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How to Incorporate Lyrics Into an Essay

Lyrics can be effective tools in an essay. You may want to cite lyrics, because a song writer says something in an eloquent way, or the excerpt solidifies a point you’re trying to make. You are allowed to quote a portion of a song under the fair use doctrine of the United States copyright law, but the law doesn’t specify exactly how many words or what percentage of a song you can use. You can use a limited portion of a song for your research paper, but it must be acknowledged though in-text citations and a listing in your works cited or reference page.

Quotations and In-Text Citations

When incorporating lyrics into an essay, put the lyrics inside quotation marks. Short quotations can be integrated into a sentence, such as, “In the song ‘Hey Jude,’ the Beatles sing…” followed by the lyrics in quotation marks.

Long quotations, or those that are four lines or longer, need to be set off in a block quote, where you indent the entire quote from the paragraph above it. To cite the lyrics in Modern Language Association format, write the artists’ name in parentheses, such as (The Beatles), followed by the ending punctuation.

To cite in American Psychological Association format, include the artist, copyright date and track number in parentheses, such as (The Beatles, 1968, track 1). Note the comma between the artist and year and between the year and track number.

Reference List

Include the details of the recording in your works cited or references page. In MLA format, include the artist’s name, song title, album name, name of the recording manufacturer, publication date and the sound recording medium, for example:

The Beatles. “Hey Jude.” Hey Jude: The U. S. Album (italicized). Capitol, 2014. CD.

Citing this recording in APA style is slightly different, so follow the example:

The Beatles. (2014). Hey Jude. On Hey Jude: The U. S. Album (italicize the album name) [CD]. Los Angeles: Capitol (Recorded 1968).

• Purdue Online Writing Lab: In-Text Citations: The Basics
• Williams College Libraries: Media
• U. S. Copyright Office: Can I Use Someone Else's Work? Can Someone Else Use Mine?
• U. S. Copyright Office: Fair Use
• Purdue Online Writing Lab: MLA Works Cited: Other Common Sources
• Purdue Online Writing Lab: Reference List: Other Non-Print Sources

Cara Batema is a musician, teacher and writer who specializes in early childhood, special needs and psychology. Since 2010, Batema has been an active writer in the fields of education, parenting, science and health. She holds a bachelor's degree in music therapy and creative writing.

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How To Quote Song Lyrics In Writing

by Juan Chumbley December 28, 2022, 9:53 am updated April 1, 2024, 11:41 am

Song lyrics are a popular form of expression that can be found in many different mediums, from books and movies to academic writings. Quoting song lyrics in writing can be a great way to make a point, provide evidence for an argument, illustrate a concept, or add a creative element to a piece of writing. In this article, we will discuss how to quote song lyrics in writing, as well as the guidelines for using song lyrics in titles.

Quoting Song Lyrics in Writing

When quoting song lyrics in writing, it’s important to cite the source correctly. Depending on the style guide you’re using, the format for citing song lyrics may vary.

Citing Song Lyrics in MLA Format

When citing song lyrics in MLA format, it’s important to include the artist’s name, the title of the song, the album the song was released on, the year the song was released, and the medium of the song (CD, Vinyl, etc.). For example:

“Bohemian Rhapsody,” Queen, A Night at the Opera, 1975, CD.

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35 future cars set to hit the market until 2028: supercars that will redefine innovation, 12 pieces of donald trump car collection: former president’s 2m$ luxury vehicles, citing song lyrics in apa format.

When citing song lyrics in APA format , it’s important to include the artist’s name, the title of the song, the year the song was released, and the medium of the song (CD, Vinyl, etc.). For example:

Queen. (1975). “Bohemian Rhapsody.” A Night at the Opera. CD.

Citing Song Lyrics in Chicago Format

When citing song lyrics in Chicago format, it’s important to include the artist’s name, the title of the song, the album the song was released on, the year the song was released, and the medium of the song (CD, Vinyl, etc.). For example:

Queen. “Bohemian Rhapsody.” A Night at the Opera. 1975. CD.

Quoting Song Lyrics in Text

When quoting song lyrics in text, it’s important to introduce the quote , including the artist’s name, the title of the song, the year the song was released, use quotation marks around the lyric, include the page number or time stamp, and, if applicable, include the verse number. It’s also important to explain the context of the lyric and how it relates to the overall message of the song.

Quoting Song Lyrics in a Sentence

When quoting song lyrics in a sentence, it’s important to introduce the quote, including the artist’s name, the title of the song, the year the song was released, use quotation marks around the lyric, include the page number or time stamp, and, if applicable, include the verse number. Additionally, it’s important to explain the significance of the lyric and how it relates to the overall message of the song. For example:

As Queen sings in “Bohemian Rhapsody” (1975), “Nothing really matters to me” (3:50). This lyric is significant because it reflects the theme of the song, which is about living life to the fullest and not worrying about the opinions of others.

Quoting Song Lyrics in a Paragraph

When quoting song lyrics in a paragraph, it’s important to introduce the quote, including the artist’s name, the title of the song, the year the song was released, use quotation marks around the lyric, include the page number or time stamp, explain the context and significance of the lyric, and, if applicable, include the verse number. Additionally, it’s important to provide an analysis of the lyric and how it relates to the overall message of the song. For example:

In Queen’s 1975 hit single “Bohemian Rhapsody,” Freddie Mercury sings, “Nothing really matters to me” (3:50). This lyric is significant because it reflects the theme of the song, which is about living life to the fullest and not worrying about the opinions of others. The lyric implies that Mercury is advocating for a life free from the constraints of societal expectations and norms.

Using Song Lyrics in Titles

When using song lyrics in titles, it’s important to follow certain guidelines. It’s important to use quotation marks around the lyrics, including the artist’s name, the title of the song, and the year the song was released. Additionally, it’s important to make sure that the song lyrics are relevant to the title and accurately reflect the overall message of the piece of writing. For example:

“Bohemian Rhapsody” by Queen (1975): A Reflection on Living Life Free from Societal Expectations

Using Song Lyrics in Academic Writing

When using song lyrics in academic writings, it’s important to be aware of the potential implications of quoting song lyrics. Song lyrics can be used to support an argument or illustrate a concept, but it’s important to be aware of the potential for misinterpretation or misuse. Additionally, when quoting song lyrics in academic writing, it’s important to provide an analysis of the lyrics and how they relate to the overall message of the piece of writing.

In conclusion, quoting song lyrics in writing can be an effective way to make a point, provide evidence for an argument, illustrate a concept, or add a creative element to a piece of writing. When quoting song lyrics in writing, it’s important to cite the source correctly, depending on the style guide you’re using. When quoting song lyrics in text, it’s important to introduce the quote, including the artist’s name, the title of the song, the year the song was released, use quotation marks around the lyric, include the page number or time stamp, explain the context and significance of the lyric, and, if applicable, include the verse number.

When using song lyrics in titles, it’s important to use quotation marks around the lyrics, including the artist’s name, the title of the song, and the year the song was released. Additionally, it’s important to make sure that the song lyrics are relevant to the title and accurately reflect the overall message of the piece of writing. When using song lyrics in academic writing, it’s important to be aware of the potential implications of quoting song lyrics and provide an analysis of the lyrics and how they relate to the overall message of the piece of writing. Of course, if you still experience problems with quoting songs, you better read the article again or ask specialists from https://academichelp.net/essay-writing-services/paperhelp-review.html

To sum it up, quoting song lyrics in writing can be a great way to add emphasis to a point, provide evidence for an argument, illustrate a concept, or add a creative element to a piece of writing. However, it’s important to cite the source correctly, introduce the quote, explain the context and significance of the lyric, and, when using song lyrics in titles or academic writing, make sure the lyrics are relevant to the title and accurately reflect the overall message of the piece of writing.

how to Lyrics quote song Writing

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Q. How should I reference song lyrics in APA Style?

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Answered By: Theresa Bell (she/her/hers) Last Updated: Nov 02, 2021     Views: 145937

APA Style (7th ed.)

If you retrieved the lyrics directly from listening to the song, reference the song using the following general example:

Lastname, A. (year). Title of song [Song]. On Title of album. Record Label.

• In-text citation: (Lastname, year, timestamp)

Lastname, A. (year). Title of song [Song]. On Title of album . Record Label. URL

• Provide the name of the recording artist for modern music and the name of the composer for classical music (APA, 2020, p. 341).
• "Include a URL in the reference if that location is the only means of retrieval (e.g., for artists who provide music in only one locations, such as SoundCloud or on their website)" (APA, 2020, p. 345)

If you retrieved the lyrics from a YouTube video , sheet music, or a web page , please use the formatting shown in those linked resources to reference the lyrics.

American Psychological Association. (2020).  Publication manual of the American Psychological Association  (7th ed.). https://doi.org/10.1037/0000165-000

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How do I cite published song lyrics from a musical?

Note: This post relates to content in the eighth edition of the MLA Handbook . For up-to-date guidance, see the ninth edition of the MLA Handbook .

To cite published song lyrics, follow the MLA format template . Note that the way you cite published lyrics will depend on how you accessed them and what information is provided by the source.

For example, the website  ST Lyrics contains an audio version of “The Story of Lucy and Jessie,” as well as printed lyrics. To cite the printed lyrics, begin the entry with the title since no author is given. Then provide the name of the website as the title of the container and list any relevant publication details. In the optional-element slot at the end of the entry, indicate the format so that your reader knows you are citing the text rather than the audio:

 “The Story of Lucy and Jessie.” ST Lyrics , 2018, www.stlyrics.com/lyrics/follies/thestoryoflucyandjessie.htm. Lyrics.

Alternatively, you may use a description in place of a title to indicate that you are citing the text of the lyrics:

Lyrics to “The Story of Lucy and Jessie.” ST Lyrics , 2018, www.stlyrics.com/lyrics/follies/thestoryoflucyandjessie.htm.

If, however, your source for the lyrics was the playscript shown below, which lists Stephen Sondheim as the author of the song’s music and lyrics, you would list Sondheim’s name in the “Author” slot, the title of the script in the “Title of container” slot, and James Goldman (the author of the script) in the “Other contributors” slot. Then list the publication details for the script:

Sondheim, Stephen. “The Story of Lucy and Jessie.” Follies , by James Goldman, Theatre Communications Group, 2001, pp. 78-80.

To learn more about how to cite lyrics, see our post on citing lyrics you heard from a song in a musical .

How to Write Lyrics in an Essay

Kimberley mcgee, 24 jun 2018.

They're effective tools and can elicit a certain type of mood in an eloquent way. Citing lyrics in an essay can purvey points that bring home the theme of the essay and add ambiance to an argument. Aside from putting them in quotation marks, possibly italics if deemed necessary, there are a few important rules to understand when quoting lyrics in an essay.

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• Copyright Law
• How to Cite Lyrics in a Paper
• To Quote or Paraphrase

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1 Copyright Law

Lyrics are allowed to be quoted, with a few exceptions. Under the fair use doctrine of the United States copyright law, a phrase, bridge or section of a song can be quoted in small portions. The law isn’t specific as to the percentage of words from the song you can use or how many words in total you can quote from a particular song in the text.

2 How to Cite Lyrics in a Paper

A research paper that isn’t publicly published can use a limited portion of a song to convey a point. Acknowledgment of the author of the song, not just the artist, is required to be included with in-text citations. The reference page of the paper needs to also include the artist, author (if different from the performer) and album name, if applicable. A CD reference requires the quote of the passage followed by a reference to the author and the CD title. This can be done in the essay and then referenced in the works-cited-list entry. The works-cited-list entry requires the artist or author of the song lyrics, album name as the source title, the publisher and date that the album was released for public consumption followed by the form it was published in, such as CD or MP3. If the lyrics chosen to highlight a point in the essay are from a website, provide a description rather than a title. Follow that with the official name of the website and any publication date or information connected to the quotes being published on that site. Attach the URL to the end of the listing with proper punctuation for the entry.

3 To Quote or Paraphrase

A direct quote should be distinct so as not to bore the reader and clutter the essay with unneeded words. Sometimes, quotes can break up the persuasive flow of a paper’s point. A block of quoted text, particularly if it's one that's popular with a large percentage of the population, can bore the reader. In this case, use the most influential part of the quote and move onto paraphrasing the rest to bring the reader back to the unique voice of the essay’s author. Don’t lean on quotes to express your views. Paraphrasing allows you to let your voice come through while relating to the reader through well-known lyrics.

• Use care when including quotations and lyrics in an essay. Adding too many quotations has the effect of interrupting the flow of the text, and it may also lead instructors to scrutinize your work for possible plagiarism.
• 1 MLA Style Center: How do I cite song lyrics?
• 2 Case Western Reserve: Quote vs. Paraphrase

About the Author

Kimberley McGee is an award-winning journalist with 20+ years of experience writing about education, jobs, business and more for The New York Times, Las Vegas Review-Journal, Today’s Parent and other publications. She graduated with a B.A. in Journalism from UNLV. Her full bio and clips can be seen at www.vegaswriter.com.

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Q. How do I cite song lyrics in Chicago?

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Answered By: Katie Hutchison Last Updated: Dec 04, 2018     Views: 54613

APA and Chicago Style  

Cite the parenthetical reference for the lyrics using APA style. Include the song title in quotation marks and in parentheses state the writer's last name, the copyright year and the track number if this is available. Using our example from Step 2 in the previous section, the in-text reference will be "Writing is My World" (Lyrics, 2006).  

Include the writer's name, copyright year, song title, album title (italicized) and the website in the reference when using APA Style. Using our example, the entry will appear in the reference list as follows: Lyrics, T. (2006). Writing is My World. Reflections (italicized). Retrieved from  http://www.thomaslyrics.com  

Cite the song using Chicago Style as a footnote. Include the superscript numeral in the text before hyphens and at the end of a sentence, clause or quotation. Use the normal size number in the footnote followed by a period. Assuming the details in Section 1, the footnote is as follows: 1. Thomas Lyrics, Writing is My World (italicized) (New York: Meditation Records, 2006),  http://www.thomaslyrics.com  

Include the song in the bibliographic reference for Chicago Style using the same detail that was included in the footnote. Begin with the artist's last name and include the publishing details without using parenthesis as was done in the footnote. Use periods to separate the elements. Using our example, cite the entry in the bibliography as follows: Lyrics, Thomas. Writing is My World (italicized). New York: Meditation Records, 2006.  http://www.thomaslyrics.com  

(Retrieved from https://penandthepad.com/cite-song-lyrics-online-source-4116.html "How Do I Cite Song Lyrics from and Online Source?" 10/26/16) 

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• You can find Hindi song lyrics here: http://www.lyricshawa.com/. You can also found Punjabi songs. by Kaka on Nov 20, 2017

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Home / Guides / Citation Guides / APA Format / How to Cite a Song in APA

How to Cite a Song in APA

Understanding how to cite songs in APA is crucial for projects that study pop culture, sociology, and a variety of other topics. This guide will show you how to cite songs following the guidelines for APA 7th edition.

Guide Overview

Citing a song, citing an album, citing a classical music album, citing an album that has been reissued or re-recorded.

• In-text citations

Reference list entry structure:

Songwriter last name, F. M. (Copyright year). Song title [Recorded by F.M. Last (performer’s name/musical group)]. On Album title [Medium of recording]. Record label name.

Note:  If the songwriter and performer are the same person , leave out the bracketed data [Recorded by _______] following the song title.

Turner, A. (2013). Do I wanna know? [Recorded by Arctic Monkeys]. On AM [Album]. Domino Records.

In-text citation structure & example:

(Songwriter last name, Year)

(Turner, 2013)

Citing a song retrieved online

Songwriter last name, F. M. (Copyright year). Song title [Recorded by F.M. Last (performer’s name/musical group)] [Lyrics]. Retrieved from URL

Reference list entry example:

Simon, P. (1972). Me and Julio down by the schoolyard [Lyrics]. Retrieved from https://youtu.be/JVdlpZ4M-Hw

Recording Artist or Group. (Date). Album title in sentence case [Album]. Record label name.

Reference list entry examples:

Abdul, P. (1992). Forever your girl [Album]. Virgin Records US.

King Gizzard and the Wizard Lizard. (2019). Infest the rat’s nest  [Album]. ATO Records.

(Recording artist last name, Year)

(Abdul, 1992)

(King Gizzard and the Wizard Lizard, 2019)

For a classical music album, write the name of the composer as the author and the individuals/group who recorded the album in square brackets after the album title. At the end of the reference, include the original date of publication.

Composer last name, F. M. (Date). Album title in sentence case.  [Album recorded by group/last name, F. M.]. Recording label. (Original work published date)

Hopkins, A. (2011). And the waltz goes on. [Album recorded by A. Rieu & Johann Strauss Orchestra]. Decca. (Original work published 1725)

For albums that have been rerecorded or reissued, include the original publication, write a slash, then include the date of the version you are using.

(Composer last name, Year)

(Hopkins, 1725/2011)

Include the original date of publication in paratheses after the recording label.

Recording Artist or Group. (Date). Album title in sentence case.  [Album recorded by group/last name, F. M.]. Recording label. (Original work published date)

The Rolling Stones. (2015). Sticky fingers [Album]. UMe. (Originally published 1971)

(The Rolling Stones, 1971/2015)

APA Formatting Guide

APA Formatting

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To cite a song or music video in APA style, you need to have basic information including the name of the composer, title of the song or music, company name, and publication date. The templates for in-text citation and reference list entry of a song or music video, along with examples, are given below:

In-text citation template and example:

In parenthetical citations, use the composer’s surname and the publication year.

Composer’s Surname (Publication Year)

Beyoncé (2013)

Parenthetical

(Composer’s Surname, Publication Year)

(Beyoncé, 2013)

Reference list entry template and example:

Songwriter F.M. (Copyright year). Song title [Recorded by F.M. Last (performer’s name/musical group)]. On Album title [Medium of recording]. City, State of label: Record label name.

Beyoncé. (2013). Ring off. On Beyoncé: Platinum Edition [MP3 file]. Los Angeles, CA: Parkwood; Columbia.

To cite lyrics in APA format, you need to have basic information including the name of the composer, title of the song, company name, date, and URL. The templates for in-text citation and reference list entry of lyrics, along with examples, are given below:

(Composer’s Surname, Publication Year, timestamp)

(Beyoncé, 2019, 02:36)

Beyoncé. (2019). Don’t jealous me. On Beyoncé: Platinum Edition [MP3 file]. Los Angeles, CA: Parkwood; Columbia.

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A Guide to Lyric Essay Writing: 4 Evocative Essays and Prompts to Learn From

Poets can learn a lot from blurring genres. Whether getting inspiration from fiction proves effective in building characters or song-writing provides a musical tone, poetry intersects with a broader literary landscape. This shines through especially in lyric essays, a form that has inspired articles from the Poetry Foundation and Purdue Writing Lab , as well as become the concept for a 2015 anthology titled We Might as Well Call it the Lyric Essay.  

Put simply, the lyric essay is a hybrid, creative nonfiction form that combines the rich figurative language of poetry with the longer-form analysis and narrative of essay or memoir. Oftentimes, it emerges as a way to explore a big-picture idea with both imagery and rigor. These four examples provide an introduction to the writing style, as well as spotlight tips for creating your own.

1. Draft a “braided essay,” like Michelle Zauner in this excerpt from Crying in H Mart .

Before Crying in H Mart became a bestselling memoir, Michelle Zauner—a writer and frontwoman of the band Japanese Breakfast—published an essay of the same name in The New Yorker . It opens with the fascinating and emotional sentence, “Ever since my mom died, I cry in H Mart.” This first line not only immediately propels the reader into Zauner’s grief, but it also reveals an example of the popular “braided essay” technique, which weaves together two distinct but somehow related experiences. 

Throughout the work, Zauner establishes a parallel between her and her mother’s relationship and traditional Korean food. “You’ll likely find me crying by the banchan refrigerators, remembering the taste of my mom’s soy-sauce eggs and cold radish soup,” Zauner writes, illuminating the deeply personal and mystifying experience of grieving through direct, sensory imagery.

2. Experiment with nonfiction forms , like Hadara Bar-Nadav in “ Selections from Babyland . ”

Lyric essays blend poetic qualities and nonfiction qualities. Hadara Bar-Nadav illustrates this experimental nature in Selections from Babyland , a multi-part lyric essay that delves into experiences with infertility. Though Bar-Nadav’s writing throughout this piece showcases rhythmic anaphora—a definite poetic skill—it also plays with nonfiction forms not typically seen in poetry, including bullet points and a multiple-choice list. 

For example, when recounting unsolicited advice from others, Bar-Nadav presents their dialogue in the following way:

I heard about this great _____________.

a. acupuncturist

b. chiropractor

d. shamanic healer

e. orthodontist ( can straighter teeth really make me pregnant ?)

This unexpected visual approach feels reminiscent of an article or quiz—both popular nonfiction forms—and adds dimension and white space to the lyric essay.

3. Travel through time , like Nina Boutsikaris in “ Some Sort of Union .”

Nina Boutsikaris is the author of I’m Trying to Tell You I’m Sorry: An Intimacy Triptych , and her work has also appeared in an anthology of the best flash nonfiction. Her essay “Some Sort of Union,” published in Hippocampus Magazine , was a finalist in the magazine’s Best Creative Nonfiction contest. 

Since lyric essays are typically longer and more free verse than poems, they can be a way to address a larger idea or broader time period. Boutsikaris does this in “Some Sort of Union,” where the speaker drifts from an interaction with a romantic interest to her childhood. 

“They were neighbors, the girl and the air force paramedic. She could have seen his front door from her high-rise window if her window faced west rather than east,” Boutsikaris describes. “When she first met him two weeks ago, she’d been wearing all white, buying a wedge of cheap brie at the corner market.”

In the very next paragraph, Boutskiras shifts this perspective and timeline, writing, “The girl’s mother had been angry with her when she was a child. She had needed something from the girl that the girl did not know how to give. Not the way her mother hoped she would.”

As this example reveals, examining different perspectives and timelines within a lyric essay can flesh out a broader understanding of who a character is.

4. Bring in research, history, and data, like Roxane Gay in “ What Fullness Is .”

Like any other form of writing, lyric essays benefit from in-depth research. And while journalistic or scientific details can sometimes throw off the concise ecosystem and syntax of a poem, the lyric essay has room for this sprawling information.

In “What Fullness Is,” award-winning writer Roxane Gay contextualizes her own ideas and experiences with weight loss surgery through the history and culture surrounding the procedure. 

“The first weight-loss surgery was performed during the 10th century, on D. Sancho, the king of León, Spain,” Gay details. “He was so fat that he lost his throne, so he was taken to Córdoba, where a doctor sewed his lips shut. Only able to drink through a straw, the former king lost enough weight after a time to return home and reclaim his kingdom.”

“The notion that thinness—and the attempt to force the fat body toward a state of culturally mandated discipline—begets great rewards is centuries old.”

Researching and knowing this history empowers Gay to make a strong central point in her essay.

Bonus prompt: Choose one of the techniques above to emulate in your own take on the lyric essay. Happy writing!

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Mastering the Art of Incorporating Song Titles in Your Essays

When it comes to writing essays, incorporating song titles can add depth and context to your work. However, knowing how to correctly format and use song titles is crucial. In this guide, we'll explore the ins and outs of writing song titles in essays.

Table of Contents

The Importance of Proper Formatting

Why correct formatting matters.

Properly formatting song titles in your essays serves several essential purposes. It not only adds clarity and professionalism to your work but also distinguishes the titles from the rest of the text.

Standard Practices for Song Titles in Essays

Italicizing song titles.

The most common practice for including song titles in essays is to italicize them. This convention helps set the titles apart and ensures that they are easily recognizable.

Examples for Clarity

For instance, if you're discussing the song "Imagine" by John Lennon, you should write it as: In his song "Imagine," John Lennon explores...

Capitalization Rules

Proper capitalization.

When writing song titles, it's important to capitalize the principal words. This includes nouns, pronouns, verbs, adjectives, and adverbs. Articles, conjunctions, and prepositions are usually in lowercase unless they are the first or last word of the title.

Applying Capitalization Rules

In the song title "Blowin' in the Wind," you would capitalize 'Blowin'' and 'Wind,' but 'in' and 'the' are in lowercase.

Dealing with Quotation Marks

Quoting song titles.

In certain cases, you may need to use quotation marks instead of italics to emphasize song titles, especially if you're using a style guide that recommends this format.

Handling Song Lyrics

Quoting song lyrics.

When quoting lyrics within your essay, use quotation marks for lyrics. Additionally, follow the conventions for citing lyrics accurately.

Adhering to Citation Styles

Mla, apa, chicago, and more.

Different citation styles (MLA, APA, Chicago) may have slight variations in rules for song title formatting. Always consult the specific guidelines of the style you're using.

Maintaining Consistency

Regardless of the style, maintain consistency in formatting throughout your essay. Whether you italicize or use quotation marks, be uniform.

Final Checks

Proofreading and review.

After completing your essay, proofread it to ensure that all song titles and lyrics are correctly formatted. Consistency in formatting contributes significantly to the professionalism of your work.

Frequently Asked Questions: Writing Song Titles in Essays

The standard practice for including song titles in essays is to italicize them. This helps distinguish them from the rest of the text.

In some cases, style guides recommend using quotation marks for song titles instead of italics. Check the specific guidelines you're following.

Capitalize the principal words in the song title, including nouns, pronouns, verbs, adjectives, and adverbs. Articles, conjunctions, and prepositions are usually in lowercase unless they begin or end the title.

If your essay discusses a song title within another title, such as an album or movie title, use quotation marks for the song title and italics for the larger work.

While citation styles like MLA, APA, and Chicago have specific guidelines, the standard practice of italicizing or using quotation marks for song titles remains consistent across these styles. Refer to the style guide you're using for specifics.

Yes, you can include song lyrics in your essay, but they should be enclosed in quotation marks and properly cited following your chosen citation style.

Yes, proofreading is essential to ensure all song titles are correctly formatted and consistent throughout your essay. Consistency enhances the overall quality of your work.

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How to Quote Song Lyrics in an Essay

When writing an essay that involves discussing or analyzing song lyrics, it is important to properly quote and cite the lyrics in order to give credit to the original artist and avoid plagiarism. However, quoting song lyrics can be a bit tricky, as there are specific guidelines that need to be followed. This comprehensive guide will provide you with the necessary information to properly quote song lyrics in your essay.

1. Use quotation marks: When quoting song lyrics, it is important to enclose the lyrics in quotation marks. This helps to clearly indicate that the words being used are not your own, but rather are from a song. For example, “I believe I can fly” is a line from the song “I Believe I Can Fly” by R. Kelly.

2. Include the artist’s name and song title: In addition to using quotation marks, it is also important to include the name of the artist and the title of the song. This provides proper attribution and allows readers to easily locate the song if they are interested. For example, “I believe I can fly” (R. Kelly, “I Believe I Can Fly”).

3. Use the correct formatting: When including song lyrics in your essay, it is important to use the correct formatting. Generally, this means using a blockquote format, where the lyrics are indented and in a separate paragraph from the rest of the essay. This helps to visually differentiate the lyrics from the rest of the text and makes them stand out to the reader.

In conclusion, properly quoting song lyrics in an essay is an important skill to master. By following these guidelines – using quotation marks, including the artist’s name and song title, and using the correct formatting – you can ensure that you are giving credit where it is due and avoiding plagiarism. Remember, it is always better to be safe than sorry, so take the time to properly quote and cite song lyrics in your essay.

Table of Contents

Why is it important to quote song lyrics properly?

Properly quoting song lyrics in an essay is important for several reasons. Here are some key reasons why it is essential to quote song lyrics properly:

• Respecting copyright laws: When using song lyrics in your essay, it is crucial to respect copyright laws. By properly quoting the lyrics, you acknowledge and give credit to the original artist and songwriter, ensuring that their work is protected.
• Avoiding plagiarism: Quoting song lyrics properly helps you avoid plagiarism. By accurately citing the lyrics, you demonstrate that you are using someone else’s work with permission, preventing any accusations of plagiarism.
• Maintaining academic integrity: Properly quoting song lyrics demonstrates your commitment to academic integrity. It shows that you have done your research, properly attributed the lyrics, and are using them as evidence to support your arguments or analysis.
• Providing context: When you quote song lyrics properly, it allows readers to understand the context of your analysis. By providing the exact words of the lyrics, you ensure that your interpretation and analysis are accurate and not lost in translation.
• Enhancing credibility: Quoting song lyrics properly adds credibility to your essay. It shows that you have taken the time to engage with the material, understand the lyrics, and provide accurate references to support your ideas.

Overall, by quoting song lyrics properly, you demonstrate your respect for the original artist, copyright laws, and academic integrity. It allows you to effectively incorporate lyrics into your essay while maintaining credibility and avoiding plagiarism.

Understanding copyright laws and fair use

When quoting song lyrics in an essay, it is important to understand the copyright laws and fair use guidelines to ensure that you are not infringing on the rights of the song’s copyright owner. Copyright laws exist to protect the original work of creators, including songwriters and musicians, and it is crucial to respect their intellectual property.

What is copyright?

Copyright is a legal protection that grants the creator of an original work exclusive rights over its use and distribution. This includes music, lyrics, and other artistic creations. Copyright laws give the creator the power to control how their work is used and allows them to profit from its use.

How does fair use come into play?

Fair use is a legal principle that allows certain uses of copyrighted material without the need for permission from the copyright owner. This principle is based on the concept that limited use of copyrighted material for purposes such as criticism, commentary, teaching, or research should be allowed, as long as it does not interfere with the original creator’s rights or undermine their ability to profit from their work. Fair use is determined on a case-by-case basis and depends on several factors, including the purpose and character of the use, the nature of the copyrighted work, the amount used, and the effect on the potential market for the original work.

Quoting song lyrics under fair use:

When quoting song lyrics in an essay, it is generally considered fair use if the lyrics are used for educational or critical purposes, and the quoted lyrics are reasonably necessary for your argument or analysis. It is important to limit the amount of lyrics you quote and provide proper attribution to the songwriter and copyright owner. Additionally, using the lyrics in a transformative manner, such as providing analysis or commentary, can strengthen your argument for fair use.

Obtaining permission:

In some cases, it may be necessary to obtain permission from the copyright owner to quote song lyrics, especially if the use does not fall within fair use guidelines. Contacting the copyright owner or their representatives, such as the music publisher or record label, is the appropriate step to take to seek permission for using song lyrics in your essay.

Conclusion:

Understanding copyright laws and fair use is crucial when quoting song lyrics in an essay. It is important to respect the rights of the copyright owner and abide by fair use guidelines. By quoting lyrics responsibly and providing proper attribution, you can ensure that your essay remains within legal boundaries while adding depth and support to your analysis.

How to Format Song Lyrics in an Essay

When writing an essay that includes song lyrics, it is important to properly format and cite the lyrics to ensure accuracy and avoid plagiarism. Here are some guidelines to help you format song lyrics in your essay:

• Quotation marks: Enclose the song lyrics in double quotation marks. For example: “I’ve got sunshine on a cloudy day.”
• Line breaks: Indicate line breaks in the lyrics by using a forward slash (/). For example: “I will always love you / And I hope you feel the same.”
• Italicize: Italicize the song title or album title to distinguish it from the rest of the text. For example: The song “Bohemian Rhapsody” by Queen is a classic.
• Capitalization: Follow the capitalization used in the original song lyrics. If the lyrics already use title case, maintain it in your essay. However, if the lyrics are in all caps, use standard capitalization rules. For example: “I will survive” vs. “I WILL SURVIVE.”
• Punctuation: Retain the punctuation used in the original lyrics, including any ellipses or exclamation points. For example: “I can’t get no satisfaction…”
• Attribution: Provide the artist’s name after the lyrics to give credit. You can include it in parentheses or as part of the sentence. For example: “I’ve got a feeling (by The Beatles)…
• Citing: If you are using lyrics from a published song, make sure to cite the source properly. Include the songwriter, song title, album name (if applicable), and release year. For example: “(Lennon & McCartney, “Hey Jude,” The Beatles, 1968)”.
• Indention: If quoting a longer section of song lyrics, consider indenting the lyrics and double-spacing the text to separate it from the rest of the essay. This can provide visual clarity and make it easier for the reader to distinguish between your thoughts and the lyrics.
• Consistency: As with any formatting style, consistency is key. Use the same formatting and citation style throughout your essay to maintain coherence and professionalism.

By following these guidelines, you can effectively incorporate song lyrics into your essay while maintaining accuracy and adhering to proper citation practices.

When and how to use block quotes for song lyrics

When quoting song lyrics in an essay, block quotes can be used in certain situations to emphasize the lyrics and provide a visual break from the rest of the text. Block quotes are typically used when the lyrics you are quoting are longer than four lines. Here’s how to properly use block quotes for song lyrics:

• Begin the block quote on a new line, without using quotation marks.
• Indent the entire block quote by half an inch from the left margin.
• Use double spacing throughout the block quote, with no additional spacing before or after it.
• Include the song title in italics at the beginning of the block quote, followed by the artist’s name and the album name in parentheses.
• If the lyrics contain a section break or a change in stanza, indicate it with a blank line between the sections.
• Do not include any additional punctuation within the block quote, unless it is part of the original lyrics.

Here’s an example of a properly formatted block quote for song lyrics:

Remember, block quotes for song lyrics are only necessary when the lyrics are longer than four lines. For shorter quotes, you can simply use quotation marks within your regular text formatting.

Citing song lyrics from different sources

When citing song lyrics from different sources, it’s important to follow the proper format and provide accurate information to give credit to the original artist and songwriter. Here are some guidelines to help you cite song lyrics from various sources:

• Official song lyrics websites: If you are citing song lyrics from an official song lyrics website like Genius or AZLyrics, you can simply include the website’s name and link in your citation. For example:
• “Yesterday” by The Beatles lyrics. Retrieved from https://www.azlyrics.com/lyrics/beatles/yesterday.html
• Album liner notes: If you are citing song lyrics from the liner notes of an album, provide the name of the album, the songwriter’s name, and the year of release. For example:
• “Bohemian Rhapsody” by Queen. From the album “A Night at the Opera” (1975)
• Streaming platforms: If you are citing song lyrics from a streaming platform like Spotify or Apple Music, include the name of the song, the artist’s name, and the streaming platform’s name or URL. For example:
• “Shape of You” by Ed Sheeran. Retrieved from Spotify: https://open.spotify.com/track/7qiZfU4dY1lWllzX7mPBI3
• Social media posts: If you are citing song lyrics from a social media post, include the username of the person who posted the lyrics, the song’s title, the artist’s name, and the date of the post. For example:
• @johnsmith: “I’m a believer” by The Monkees – February 20, 2022
• Personal interviews or live performances: If you are citing song lyrics from a personal interview or live performance, provide the name of the person interviewed or performing, the song’s title, and the date of the interview or performance. For example:
• John Lennon (personal interview): “Imagine” – June 6, 1971

Remember to always double-check the accuracy of the song lyrics and the source information before including them in your essay. Properly citing song lyrics not only gives credit to the original artists and songwriters but also enhances the credibility and integrity of your own work.

Examples of properly quoted song lyrics

These examples demonstrate the correct way to quote song lyrics in an essay. When quoting lyrics, it’s important to include the song title in quotation marks, the artist’s name, and the specific lyric being quoted. Additionally, lyrics should be formatted as a separate paragraph or shown as indented text to clearly distinguish them from the rest of the essay. It is also recommended to cite the source of the lyrics, such as the album or the year of release.

Question and answer:

What is the purpose of quoting song lyrics in an essay.

Quoting song lyrics in an essay serves several purposes. It can provide evidence to support an argument, enhance the overall writing style, and add depth and emotional resonance to the essay.

Do I need to get permission to quote song lyrics in my essay?

The need for permission to quote song lyrics in an essay depends on the context and purpose of the essay. If the essay is for educational or personal use, quoting a few lines is generally considered fair use. However, if the essay is for commercial use or public distribution, it is best to obtain permission from the copyright holder.

How do I properly format song lyrics in my essay?

To properly format song lyrics in an essay, you should enclose them in quotation marks and provide the artist’s name, song title, and album or source. For example, “I want to hold your hand” (The Beatles, “I Want to Hold Your Hand,” 1963).

How much of a song can I quote in my essay?

The amount of a song you can quote in your essay depends on the purpose and length of your essay. It is generally best to only quote a few lines or phrases that are directly relevant to your argument or analysis. Remember to always give credit to the artist and provide proper citation.

Can I paraphrase song lyrics instead of quoting them in my essay?

Yes, you can paraphrase song lyrics instead of quoting them in your essay. Paraphrasing involves rewording the lyrics in your own words while still conveying the same meaning. However, it is important to still give credit to the artist and provide proper citation when paraphrasing.

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• Year of distribution (in round brackets).
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• Place of distribution: distribution company.

  In-text citation:

(Lennon and McCartney, 1966) 

Reference list:

Lennon, J. and McCartney, P. (1966).  Paperback writer . Liverpool: Northern Songs, Ltd.

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Why are song lyrics becoming simpler? a time series analysis of lyrical complexity in six decades of American popular music

Michael E. W. Varnum

1 Department of Psychology, Arizona State University, Tempe, Arizona, United States of America

Jaimie Arona Krems

2 Department of Psychology, Oklahoma State University, Stillwater, OK, United States of America

Colin Morris

3 Toronto, Canada

Alexandra Wormley

Igor grossmann.

4 Department of Psychology, University of Waterloo, Waterloo, ON, Canada

Associated Data

All data and reproducible code for analyses reported in the manuscript are available on the Open Science Framework ( https://osf.io/qnsmj/ ).

Song lyrics are rich in meaning. In recent years, the lyrical content of popular songs has been used as an index of culture’s shifting norms, affect, and values. One particular, newly uncovered, trend is that lyrics of popular songs have become increasingly simple over time. Why might this be? Here, we test the idea that increasing lyrical simplicity is accompanied by a widening array of novel song choices. We do so by using six decades (1958–2016) of popular music in the United States ( N = 14,661 songs), controlling for multiple well-studied ecological and cultural factors plausibly linked to shifts in lyrical simplicity (e.g., resource availability, pathogen prevalence, rising individualism). In years when more novel song choices were produced, the average lyrical simplicity of the songs entering U.S. billboard charts was greater. This cross-temporal relationship was robust when controlling for a range of cultural and ecological factors and employing multiverse analyses to control for potentially confounding influence of temporal autocorrelation. Finally, simpler songs entering the charts were more successful, reaching higher chart positions, especially in years when more novel songs were produced. The present results suggest that cultural transmission depends on the amount of novel choices in the information landscape.

Introduction

Music is a human universal [ 1 , 2 ], and it is known to influence cognition, affect, and behavior [ 3 – 5 ]. Because songs—and particularly popular song lyrics—can be so rich in meaning [ 6 , 7 ], social scientists have long explored the ways that such lyrics intersect with some fundamental social processes, including identity formation and person perception [ 8 – 13 ].

More recently, social psychologists have begun to view music as a cultural product and to examine the ways that popular music lyrics reflect important aspects of psychology at the cultural level; the content in popular lyrics indexes changing norms, affect, and/or values [ 5 , 14 – 19 ]. For example, DeWall and colleagues explored popular song lyrics as a “window into understanding U.S. cultural changes in psychological states” [5, pp. 200], finding that popular songs lyrics from 1980–2007 reflected an increase in self-focus and a decrease in other-focus.

Here, we demonstrate that popular music lyrics have become increasingly simple over time, and we test one possible explanation for this surprising trend, namely that the amount of novel song choices has increased.

Novel song choices and lyrical simplicity

Several lines of evidence suggest that people may have baseline preferences for songs with simpler lyrics. One of the most widely known phenomena in psychology is the mere exposure effect, a phenomenon where repeated exposure to a non-aversive stimulus increases preference for it [ 20 – 22 ]. One implication of this principle for the present question is that simpler, more repetitive lyrics as these pieces essentially have this effect baked into them and thus may tend to be preferred all other things being equal. Further, songs with more repetitive lyrics may enjoy certain advantages in terms of information transmission as they are easier to remember [ 23 ] and likely easier to transmit with fidelity [ 24 – 26 ]. Further, recent work has shown that naïve listeners find simpler, more repetitive pieces of music to be more enjoyable, engaging, and memorable [ 27 , 23 ].

Why might pop songs become lyrically simpler in times when more new songs are produced? Theory and research from diverse literatures suggest that songs with simpler lyrics might be especially successful when there are more new songs to choose from. First, humans are cognitive misers. People have limited information-processing capacities [ 28 ], and are known to conserve mental resources [ 29 ]. Consequently, humans often use shortcuts in decision-making [ 30 , 31 ]. For example, when confronted with the task of evaluating persuasive messages and/or complex decision environments, people are more likely to use heuristics, peripheral cues, and other automatic cognitive processes to evaluate these messages if cognitive resources are limited in some fashion [ 32 , 33 ]. Thus, when there are more products to be evaluated, people may increasingly prefer simpler products as they may require less mental effort to engage with. The mere exposure effect might also have a greater influence on decision making in such contexts as well, given that it too can be thought of as a heuristic or even instinctive evaluation. Further, across real-world studies and in-laboratory experiments, when people are confronted with a greater number of options to choose from, they are more likely to choose simpler, less cognitively demanding products [ 34 ]. Taken together, this work suggests that pop songs on average might become lyrical simpler in times when people are exposed to greater amounts of new songs and that success of such songs might be more strongly linked to lyrical simplicity in such times.

Here, we test the hypothesis that the trend toward increasingly simple popular music lyrics might be accompanied by the increasing number of songs released each year, using six decades’ worth of song data. We also do so while including a number cultural and ecological control variables, as prior work demonstrates that well-studied ecological features, such as resource levels, pathogen threat, and sources of external threat (e.g., climatic stress, armed conflict) can impact markers of cognition and behavior at the cultural-level [ 35 – 38 ], and might plausibly affect preferences for simplicity in aesthetic products. For example, both resource scarcity and pathogen prevalence have been associated with conformity, innovation, and creativity in prior work [ 35 , 39 , 40 ].

We gathered cross-temporal data covering a period of six decades (1958–2016) on lyrical compressibility (as an index of simplicity/complexity of song lyrics), amount of novel songs produced (as an index of available novel song choices), and ecological, socioecological, and cultural variables linked to patterns of cultural change in previous research or plausibly related to trends in aesthetic content.

Lyrical compressibility of successful music

We gathered data from 14,661 songs that entered the Billboard Hot 100 charts spanning the period from 1958 (the charts inception) to 2016. The Billboard Hot 100 tracks the 100 most popular songs each week based on music sales, radio airplay, and internet streaming. To operationalize lyrical complexity (vs. simplicity), we estimated text compressibility. By operationalizing complexity via a compressibility index, we avoided some of the conceptual ambiguity associated with operationalization of complexity in prior research [ 40 – 42 ]: Whereas multi-purpose use of a single product may reflect product’s complexity from the operational standpoint, it may also represent greater simplicity from the standpoint of consumer psychology. Further, song lyrics are tractable to work with when using an automated compression algorithm.

Compressibility indexes the degree to which song’s lyrics have more repetitive and less information dense, and thus simpler, content. We used a variant of the established LZ77 compression algorithm. In brief, the LZ77 algorithm works by finding repeated substrings and replacing them with 'match' objects pointing back to the string's previous occurrence. A match is encoded as a tuple (D , L) , with D being the distance to the substring's previous occurrence, and L being its length. We treated these matches as costing 3 bytes. This way, a repeated string only leads to space savings if it is of at least length 4, and longer repetitions lead to greater relative savings. Given a song S , and the set of matches M produced by the LZ77 algorithm when applied to that song, its compressed size is therefore:

Where |S| is the original size of the song's lyrics, measured in characters/bytes. The compression ratios of songs in our dataset (i.e., | S |/ compsize(S) ) followed an approximately log-normal distribution, so we operationalized compressibility as the logarithm of this ratio:

We used the LZ77 compression algorithm because of its intimate connection to textual repetition. Most of the byte savings when compressing song lyrics arise from large, multi-line sections (most importantly the chorus, and chorus-like hooks). Another significant contributor are multi-word phrases, which may be repeated in variations across different lines for poetic effect (e.g. the anaphoric verses in Lady Gaga's Bad Romance : "I want your ugly / I want your disease / I want your everything …"). The compression may make use of repeated individual words, or even sub-word units that repeat (perhaps incidentally), but their contribution to the overall compressibility is low.

Higher compression scores signify more repetition and therefore higher simplicity. A score of 0 means no compression was possible (e.g. if the input were random noise), a score of 1 means a 50% reduction in size, a score of 2 means a 75% reduction, and so on. For example, Daft Punk’s 1997 song “Around the World” repeats the title 144 times and has a compressibility score of 5.42 (the maximum in this sample). Nat King Cole’s “The Christmas Song” (1961) has a low compression score of 0.11.

We computed mean compressibility for each year based on all songs that entered the Hot 100 charts in a given year for which we were able to scrape lyrics (1958–2016). Because we used an automated procedure for song scraping, which depends on the readability of the song lyrics, the percentage of songs scraped varied between 27% of top 100 songs in 1958 and 91% of songs in 2015 ( M = 57%, Md = 57%, SD = 19%). Because percentage of scraped songs has been increasing over time, and correlated with the compressibility index, τ = .73, p < .001, in additional analyses we controlled for this trend.

Song success

Some of the theoretical positions we draw on to evaluate possible reasons for changes in lyrical complexity suggest that more compressible songs may be more likely to be successful. To evaluate this proposition, we additionally gathered data on the highest position of each song in the sample achieved on the Billboard charts.

Novel music production

In the spirit of the multiverse analyses [ 43 ], we used three separate indicators to assess the amount of new music to which people are likely exposed in a given year. For each year (1958–2016) we computed the total number of songs which made the Hot100 chart, the number of musical releases per year according to Discogs (Discogs.com), and the number of Wikipedia entries about songs first published or performed each year (Wikipedia.org).

Possible ecological drivers of cultural change in aesthetic preferences and music production

We assessed a range of well-studied socioecological factors (e.g., resource levels, pathogen threat, sources of external threat), which could plausibly bear on aesthetic preferences or might affect lyrical simplicity (and whether the predicted association between novel music production and simplicity holds even controlling for these or other ecological and cultural variables discussed below). Resource scarcity has been linked to greater conformity [ 39 ] and cross-temporal work has found that greater resource levels are linked to more innovation and creative output [ 40 ] and less conformity [ 44 , 45 ]. Higher levels of infectious disease have also been linked to more conformity [ 46 , 47 ], traditionalism [ 48 ], and tight social norms [ 35 , 49 ]. External threats , due to climate or war, have also been linked to more traditional outlooks and tight social norms [ 49 ], which might similarly bear on trends in lyrical simplicity. We thus included publicly accessible data indexing these factors GDP per capita, GDP growth, unemployment, pathogen prevalence, climatic stress, and participation of the US in major armed conflicts. The data used in our analyses covered the years 1958–2016. Data on GDP per capita and GDP growth were gathered from macrotrends.net, and data on the other markers came from Varnum & Grossmann [ 50 ] and updates from the original data sources used in that publication.

We also explore the possible impact of other socioecological factors that might plausibly affect lyrical simplicity. One might speculate that immigration could drive increases in lyrical simplicity. For example, simpler lyrics in American pop songs might be linked to shifts in the amount of people for whom English may not be a first language. In a similar way, it might be that ethnic fractionalization , so far linked to changes in individualism and uniqueness over time [ 51 ]¸ may also increase preferences for, memory of, and/or dispersal of simpler, more repetitive lyrics, as such content would be easier to convey and understand to a wide range of audiences. To assess the possibility that a rise in simpler English lyrics might be linked to shifts in the amount of people for whom English may not be a first language, we used data on the number of green cards issued from the Department of Homeland Security as a marker of immigration. To assess possibilities linked to ethnic fractionalization, we used data on ethnic fractionalization from the US Census Bureau.

Research on the consequences of residential mobility also suggests that perhaps this variable might also affect lyrical trends. Previous studies have linked residential mobility to greater susceptibility to the mere exposure effect and greater preference for familiar cultural products [ 52 ]; thus, it may be that mobility is also linked to temporal variations in lyrical complexity of pop songs. To assess residential mobility, we gathered data on percentage of the US population that changed residence within the US from the US Census Bureau.

At the same time, a simpler variable might also be driving this effect. Perhaps products that succeed with a larger audience are merely simpler, akin to a lowest common denominator effect. Because the U.S. population grew substantially in recent decades, we also test whether population trends might be associated with lyrical simplicity. Thus, we also gathered data on the total size of the US population from macrotrends.net to explore population size.

Cultural factors

Prior work has found conservatives show a preference for simple and unambiguous art, speech patterns, and literature [ 53 – 57 ] (though see also Conway et al., 2016 [ 58 ]). Thus, one might suspect that possible changes in conservatism could be driving lyrical simplicity. Somewhat similarly, other evidence suggests that cross-cultural differences in aesthetic preferences and expression are linked to orientations toward collectivism [ 59 , 60 ]. Thus, we also gathered data on indicators of conservative ideology , operationalized conservatism as the average percent of annual survey respondents in Gallup polls identifying as conservative, and we included as an index of cultural level collectivism based on frequency of collectivism related words in the Google Ngrams American English corpus [ 45 ].

Analytic procedure

Where possible, we use non-parametric ordinal-level measures of correlation or partial correlation ( Kendall ’s rank correlation coefficient τ), which provides estimate of similarity of the orderings of the data when ranked by each of the quantities. Since Fechner’s initial work on time series analyses, Kendall ’s τ has been a preferred metric for examining cross-temporal relationships [ 61 ]. It provides a conservative estimate, which is preferred because time series data is rarely normally distributed. Results were comparable when we used Pearson’s r or partial Pearson correlations. In the initial step, we examined zero-order relationships between each of the three indices of available novel song choices and average lyrical compressibility of popular songs. Next, we created a composite index of novel song choices and assessed the robustness of the hypothesized link between amount of novel song choices and average lyrical compressibility of popular songs by controlling for a host of ecological, socioecological, and cultural factors that might plausibly influence cultural level success for simplicity vs. complexity. Our chief analyses focused on a set of corrective analyses, in which we controlled for the possibly spurious nature of the relationship between our key time series due to temporal autocorrelation.

Given the range of possibilities of correcting for temporal autocorrelation, we opted to perform three different types of analyses that correct or account for the possibility that observed relationships might be spurious as a function of autocorrelation in the time series. First, we computed adjusted significance thresholds based on the Tiokhin-Hruschka procedure [ 62 ]. Second, we detrended our novel song production and lyrical compressibility time series by residualizing for year and assessed the correlation between our detrended variables. Finally, for central univariate and multivariate analyses, we used an automated auto-regressive integrated moving average forecasting model (auto.ARIMA) to assess the relationship between novel song choices and lyrical compressibility [ 63 ]. This technique involves a machine learning algorithm that tests a number of different possible models which vary in autoregressive components, differencing, and moving average components, as well as whether they include an exogenous predictor. Additionally, we used auto.ARIMA to generate a forecast for future patterns of lyrical compressibility (2017–2046).

For multivariate analyses we entered multiple predictors of lyrical compressibility over time. To avoid multicollinearity and overfitting (and due to limited number of units at the yearly level of analysis), we first aggregated covariance scores attributed to additional socioecological and cultural factors (see Table 1 ) by performing a principal component analysis on these covariates and saving component scores for further multivariate time series analyses. The first principal component explained 50% of the variance in the covariates, with strong loadings (absolute value >.85) for Population Size, GDP/capita, Residential Mobility, Pathogen Prevalence, Ethnic Heterogeneity and Immigration, moderate loadings for Armed Conflicts (.49) and weak loading of GDP growth (.44). Other covariates (Climatic Stress, Unemployment, Conservatism, Collectivism) showed very weak loadings (.21 < absolute value ≤ .27). Next, we entered both yearly music production scores and covariate-PCA scores as independent predictors of lyrical compressibility, simultaneously accounting for the time series structure in the data.

*p < .05,

** p ≤ .01,

*** p ≤ .001.

Data availability

Indicators of novel song choices and average lyrical compressibility.

As Fig 1 indicates, mean lyrical compressibility (i.e., simplicity) of songs increased over time, Kendall’s τ = .726, p < .001, as did number of songs making the Hot 100 charts per year, Kendall’s τ = .425, p < .001, number of music releases according to Discogs per year, Kendall’s τ = .973, p < .001, and number of Wikipedia entries for songs by year of publication, Kendall’s τ = .871, p < .001.

Light purple indicates 95% confidence bands, dark purple indicates 80% confidence bands.

Analyses of the composite index of novel song choices

Hot100 songs, Discog music releases, and Wikipedia song entries were highly correlated, .41 < Kendall’s τ’s ≤ .87, and formed a single principle component with highest loadings by the Wikipedia song entries (.98), and weakest loading by the Hot 100 songs (.88). To avoid multicollinearity, we used component scores for further analyses. Overall, this index of novel music production was strongly positively related to compressibility, Kendall ’s τ = .714¸ p < .001. Consistent with our predictions, mean lyrical compressibility per year was positively correlated with amount of novel music produced per year as operationalized by three distinct indicators, Kendall’s τ ( n songs in Hot 100 charts/year) = .429, p < .001, Kendall’s τ ( n Discogs music releases / year) = .721, p < .001, Kendall’s τ ( n Wikipedia entries about songs/year) = .680, p < .001.

Relationships between socioecological factors and compressibility

Although several ecological dimensions were associated with changes in average lyrical compressibility over time (see Table 1 ), these relationships were often in the opposite direction that prior research or theorizing would suggest. For example, there were significant negative correlations between GDP per capita and pathogen prevalence and average lyrical compressibility. Further, our two cultural variables were either unrelated to lyrical compressibility (conservatism) or correlated in the opposite of the predicted direction (collectivism). We did observe theoretically sensible relationships between compressibility and residential mobility, immigration, ethnic fractionalization, and population size. However, when controlling for the potentially confounding effect of temporal auto-correlation by residualizing out the effect of year, only three of these relationships are statistically significant, and only the relationship between pathogen prevalence and average lyrical complexity remains in a theoretically sensible direction (see Table 1 ).

Robustness analyses: Control variables

This PCA-based composite index of music production remained significantly related to lyrical compressibility when including percentage of scraped songs/year as a covariate, Kendall ’s τ p = .261¸ p = .003. Further, it remained significant when controlling separately for each of the 12 specified control variables, .220 < partial Kendall’s τ’s < .770, p’s < .02 (see Table 2 for details). Full correlations between these variables are presented in S1 Fig .

Robustness analyses: Auto-correlation

Importantly, the correlation between this composite index of novel song choices and average lyrical compressibility remained significant when adjusting significance thresholds using the Tiokhin-Hruschka method to account for observed auto-correlation in the two time series, r = .877¸ corrected p < .001. As an alternative method for dealing with autocorrelation, we also detrended the time series by residualizing out the linear impact of year. The correlation for our detrended variables remained significant, Kendall’s τ = .222, p = .010.

Given the time series nature of our data, another way to test the hypothesized link between amount of new songs available and average compressibility of these songs while also addressing the issue of autocorrelation can involve an automated ARIMA algorithm (auto.ARIMA) within the forecast package [ 64 ] in R 4.0.0 [ 65 ]. This machine-learning algorithm inspects the time-series data to fit the optimal forecasting function. The auto-regressive ( AR(p) ) component refers to the use of past values in the regression equation for the series Y. The auto-regressive parameter p specifies the number of lags used in the model. A moving average ( MA(q) ) component represents the error of the model as a combination of previous error terms e t . The order q determines the number of terms to include in the model. ARIMA models are well-suited for long-term time series, such as the historic patterns in the present data. The automated algorithm within the forecast package searches through combinations of order parameters and picks the set that optimizes model fit criteria, comparing Akaike information criteria (AIC) or Bayesian information criteria (BIC) of respective models. Notably, the automated forecasting approach allows us to specify an exogenous predictor such as novel song choices, such that the automated function can evaluate the extent to which this exogenous predictor improves the fit above and beyond the decomposition of the time-series of the dependent variable. In other words, the automated function provides a conservative way to see whether an exogenous predictor such as the novel song choices index improves accuracy in forecasts of the lyrical compressibility. If the final model selected by auto.ARIMA includes our putative exogenous variable (in this case amount of novel song choices), then this suggests that this variable helps the model to achieve optimal fit to the data.

The results of this automated forecasting procedure indicated that a model with a positive autoregressive component, B = .527, SE = .124, and a positive contribution of the novel music production index, B = .059, SE = .008, provides the best fit to the data:

This model estimation suggests that the index of novel song choices contributes to average lyrical compressibility above and beyond the temporal autocorrelation observed for average lyrical compressibility. Further, the coefficient for the index of novel song choices was statistically significant, z = 6.95, p < .001.

We also ran an alternative set of auto.ARIMA analyses where we set novel song choices as the dependent variable and average lyrical compressibility as an exogenous predictor. The results of this automated forecasting procedure indicated that a model with two positive moving average components, B = 1.176, SE = .242, and B = .487, SE = .164, and a positive contribution of average lyrical compressibility, B = 5.067, SE = 2.207, provides the best fit to the data:

The coefficient for lyrical compressibility was statistically significant, z = 2.30, p = .02.

Comparison of the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values for our primary and alternative models suggest that our primary model with novel song choices as an exogenous predictor and lyrical compressibility as the dependent variable, AIC = -235.84, BIC = -227.53, is superior to the alternate model with lyrical compressibility as an exogenous predictor and novel song choices as the dependent variable, AIC = 58.36, BIC = 68.75.

Robustness analyses: Controlling for percentage of scraped songs

Because of a positive association between lyrical compressibility and percentage of scraped songs per year, we performed a separate set of analyses in which we first regressed out the effect of sampling (% of scraped songs/year) on lyrical compressibility and performed an auto.ARIMA analysis on the residuals. Results of a model on the residuals with music production as a predictor indicated a significant effect of music production, B = .799, SE = 0.046, z = 17.32, p < .001, suggesting that the effect songs even when accounting for the possible change in sampling.

Multivariate analyses

In another set of control analyses, we performed an auto.ARIMA analysis, in which we included the PCA factor formed by all socio-ecological covariates as a second covariates. By comparing the magnitude of the effect from this first principal component (which was chiefly driven by ecological variables) and music production index, we can assess the relative contribution of the music production index via-a-vis other socio-ecological covariates. The results of this automated forecasting procedure indicated that a model with a positive autoregressive component, B = .513, SE = .118, a significant positive contribution of the novel music production index, B = .038, SE = .016, z = 2.37, p = .018, and a non-significant positive trend formed by ecological covariates (and chiefly reflecting economic and population growth), B = .026, SE = .016, z = 1.61, p = .108, provides the best fit to the data:

This model estimation suggests that the index of novel song choices contributes to average lyrical compressibility above and beyond the temporal autocorrelation as well as other ecological covariates observed for average lyrical compressibility. Moreover, the effect of music production on lyrical compressibility was stronger than other feasible covariates explored in the present dataset.

Exploratory song-level analyses

In exploratory analyses we evaluated how lyrical compressibility is associated with song success, and whether this relationship was stronger in time periods when more novel music was produced. Given that we shifted focus to song-specific data, we utilized a multi-level framework via lme4 package in R , with songs’ chart position and lyrical compressibility scores nested within years. Preliminary auto.ARIMA analyses on the yearly aggregate data indicated that a model with no auto-regressive components but a linear trend would show the best model fit. Therefore, in the first multi-level model we included year as a proxy for a linear trend as well as compressibility X year interaction as predictors of song success. Both year and lyrical compressibility were mean-centered prior to analyses. This multi-level model showed a good overall model fit, R 2 = .05, with 3.9% of the variance explained by fixed effects. Results indicated a significant effect of year, B = 0.318, SE = 0.031, t ( df = 57.29) = 10.23, p < 001, suggesting that over time songs included in the sample on average had a lower chart rank—a typical regression to the mean effect. Importantly, more compressible songs showed significantly higher rank in the charts, B = - 9.321, SE = 0.661, t ( df = 14640.88) = 14.10, p < .001, and this effect was particularly pronounced for more recent years, compressibility X Year interaction, B = - 0.105, SE = 0.039, t ( df = 14581.41) = 2.71, p = .007.

In the second step, we added mean-centered yearly music production index as a second covariate, along with a music production X compressibility interaction. Based on prior auto. ARIMA results, we also included linear effect of year to account for the trend in the chart position. This multi-level model also showed a good overall model fit, R 2 = .06, with 4.7% of the variance explained by fixed effects. More compressible songs showed significantly higher rank in the charts, B = - 9.353, SE = 0.657, t ( df = 14819.95) = 14.23, p < .001. Also, average chart position of songs was higher in years with a greater volume of songs produced, B = 6.141, SE = 1.280, t ( df = 53.76) = 4.80, p < .001. Moreover, as Fig 2 indicates, lyrical compressibility was more strongly associated with song success in years with greater volume of produced songs, compressibility X music production interaction, B = - 2.170, SE = 0.648, t ( df = 14781.15) = 3.35, p = .001. These analyses yield results consistent with the proposition that lyrically simpler songs enjoy greater success in time periods in which more novel song choices are available.

Confidence bands indicate 95% around the estimate.

Forecasting

As a final step, we generated a forecast for average lyrical compressibility for four decades after the last data point in our time series. This is in keeping with recommendations by Varnum & Grossmann [ 38 ] that papers analyzing past patterns of cultural change provide forecasts for the future. These forecasts enable a test of this theoretical model against concrete future cultural trends. Using the automated ARIMA algorithm, we also identified the best function for the novel song choices data, which we used to estimate the subsequent 40 data points. In turn, we used this estimated data in conjunction with the compressibility function to forecast the further development of lyrical compressibility. Results of this model suggest that lyrical compressibility will continue to increase over the next several decades (see Fig 1 ).

Popular music lyrics have recently been used to inform work on the cultural transmission of emotional expression [ 14 , 66 ], as an index of culture-level changes in self- versus other-focus [ 5 ], and as a reflection of cultural mood in respond to economic and social threats [ 18 , 19 ]. But one major trend in popular music lyrics remained underexplored and unexplained—popular music lyrics are coming increasingly simple over time. We reasoned and found support for the hypothesis that increasing lyrical simplicity is associated with increasing amounts of novel music production. That is, in times when more novel music is produced, popular songs become increasingly lyrically simple.

The relationship between mean lyrical compressibility and the amount of novel music produced each year was robust. We observed significant positive associations across three operationalizations of the amount of novel song choices and the average lyrical compressibility of popular songs. Further, the relationship between amount of novel song choices and average compressibility of popular songs remained significant when including a host of ecological, socioecological, and cultural factors linked to other types of cultural change both in univariate and multivariate analyses. By and large these other variables were not significantly associated with changes in lyrical simplicity after controlling for the potentially confounding influence of temporal autocorrelation. Of note, we also observed a significant negative association between changes in pathogen prevalence and lyrical simplicity. This observation suggests a potentially new consequence of infectious disease threat, one that should be explored in more detail in future work.

Importantly, the linkage between amount of new music produced and average compressibility of popular songs also held when accounting for temporal autocorrelation using three distinct methods. Thus, results suggest that the amount of novel music produced contributes to changes in average lyrical compressibility above and beyond other plausible causes and autoregressive trends in the data.

In exploratory analyses, we also found evidence suggesting that success, as indexed by position in the billboard charts, among popular songs was associated with greater lyrical compressibility. This is broadly consistent with the notion that simpler content enjoys an advantage in memorability and/or transmission. Importantly, this effect appeared to be stronger in years when the amount of novel songs produced was higher, providing conceptual confirmation of our key finding. More novel song choices appear linked to both greater average lyrical compressibility of the body of songs that succeeds (i.e., those entering the billboard chart in a given year), and, among songs entering the charts in a given year, compressibility was more strongly associated with better performance on the chart in years when more novel songs were produced.

This finding might parallel ongoing research taking information-theoretic approaches in exploring communicative efficiency in human language [ 67 , 68 ]. For example, in both language and music, something akin to Zipf’s law seems to be at play [ 2 ]—i.e., the frequency rank of a phenomenon is inversely proportional to its probability, such that, in the case of language, many words are quite rare, but a few words (e.g., pronouns) appear with great frequency. Moreover, these more successful (i.e., frequently-used) words tend be shorter in length (but see also Piantadosi et al., 2011 [ 69 ]). This observation dovetails with our finding regarding the success of simpler lyrics. Indeed, the increasingly success of simple lyrics may reflect increasing communicative efficacy.

A preference for simpler information in increasingly information-saturated environments might also be consistent with some propositions from cultural evolutionary theory. One tenet of cumulative cultural evolutionary theory is that human innovation, transmission, and learning increase the amount and quality of cultural information, while also increasing the learnability of this information [ 70 , 25 ]. One way to increase information learnability is via simplicity [ 71 , 72 ], thereby yielding increasingly efficient communication.

The present report adds to two growing bodies of empirical research—work emphasizing the examination of cultural products as a window into cultural-level psychological processes [ 14 , 5 ] and work using time-series methods to test hypotheses regarding the causes of particular patterns of cultural change (for a review see Varnum & Grossmann, 2017 [ 38 ]). Here, we use big data and time series methods to show that increases in the amount of novel songs over time appear to be linked to the increasing simplicity of popular songs’ lyrics, as well as greater success of songs with simpler lyrics. What does this tell us more broadly about how American culture has changed? It suggests potentially that success of aesthetic complexity at the cultural level may be something that shifts over time. Although this is not the first such demonstration of this phenomenon, to our knowledge this is the first attempt to formally evaluate why such cultural-level preferences may change.

Alternative and complementary explanations

Although we found that our key effect was highly robust, alternative or complementary explanations for the growing success of lyrically simpler songs are still possible. For example, changes in the ways that people consume popular music could perhaps affect lyrical simplicity. Technological innovation (e.g., various portable music devices) could play a role, as could other variation in the ways that people interact with music. Relatedly, one might speculate that the success of increasingly simple lyrics might owe to technologically mediated increases in listening to music primarily in the background (e.g., on commutes, in gyms). However, one might easily argue that for generations music has been consumed in this fashion albeit with slightly different technologies—portable radios, car stereos, and portable music players have existed and been widely used for decades. It would be interesting to attempt to assess this question empirically, although we are not currently aware of high-quality time series data relating to how and why people listen to popular music. Moreover, operationalization of these indicators of technological innovations over time would be a potentially thorny problem. For instance, what does it mean to own a Walkman in 1982 as compared to a similar device in 2002? Nonetheless, it would be intriguing to assess these questions in future work.

Another possibility is that the length of songs may have changed over time affecting average lyrical complexity. Thus, perhaps song lyrics are more compressible by virtue of songs becoming shorter. However, a recent analysis of songs entering the Billboard charts over the course of its history suggests, in fact, that the average song on the charts in the late 2010’s was somewhat longer than those in the 1950’s and 1960’s, and similar in recent years to levels observed in the 1970’s [ 73 ]. Thus, this alternative explanation cannot account for the trends observed in the present analyses.

One might alternatively speculate that the rise in lyrical simplicity observed in the present data might be related to trends in the popularity of different musical genres. Indeed, although this is beyond the scope of the present work, it would be interesting to empirically assess how lyrical complexity varies across popular music genres and whether trends within these genres over time have been similar. Further, future work might assess whether the linkage between lyrical simplicity and song success observed in our exploratory analyses varies within genres of popular music or if genres that are on average simpler enjoy greater success in times of more music production.

Limitations

It is worth noting that our analysis was restricted to a single type of cultural product. It might be the case that empirical analysis of other domains might show similar trends and a similar relationship between amount of novel content and success of simpler content, or it may be that different dynamics are observed when considering television shows, videogames, or other types of cultural products. For example, many have argued that television shows have become more complex and intellectually stimulating in the past few decades, entering the so-called “Golden Age of Television.” However, empirical work examining complexity over time in other types of cultural products, including movies, news broadcasts, print newspapers, novels, and political speech suggests that there is in fact a broad trend toward simpler content being increasingly preferred, at least when it comes to the language used in these products [ 74 ]. It is noteworthy that Jordan and colleagues (2019) used a different measure of complexity, in this case use of a specific set of words indicate cognitive complexity, and that they find that the strength of the decline in complexity varies across different types of cultural products. Hence, future research may attempt to conceptually replicate our work by assessing compressibility of other types of cultural products over time and whether the success of such products is linked to the number of options or alternatives within that domain.

It is also worth noting that, in the present work, we assessed the simplicity of lyrics. Songs might be complex or simple in other ways as well, in terms of rhythm, melody, number of instruments played, and so on. Analyses of these features is beyond the scope of the present work, but it would be interesting to see the extent to which similar or divergent patterns are observed in these facets of successful popular music over time.

Our analysis was also limited to songs that were relatively successful over time—i.e., those that made the Billboard Hot 100 chart. This sample is quite large ( N > 14,000), but it may not be representative of all songs produced during this period. Further, we were able to successfully scrape a greater proportion of more recent rather than older songs, which we included in control analyses. Our sample captures a large chunk of popular music produced during more than half a century and enables tests regarding linkages between novel music choices, lyrical simplicity, and song success. A slightly different conceptual question may be worthwhile addressing in future work: Does average complexity of all music produced change along with shifts in the amount of music produced?

Our work is also limited by the fact that song success was operationalized by commercial success in the US market. Although some cultural shifts in the past several decades appear to be global in nature, such as rising individualism [ 36 ], this need not be the case for all dimensions of culture. Different dynamics may potentially be observed in terms of song success in parts of the world with different values, practices, and ecological conditions. Although such an endeavor is beyond the scope of the present manuscript largely due to the lack of equally rich time series data from other countries, it would be worthwhile to try to address this question in the future.

Finally, the present work is limited by its correlational nature. Although our findings appeared quite robust across different operationalizations of the independent variable—when accounting for autocorrelation in various ways, and when controlling for a host of plausible ecological, socioecological factors, and cultural values which have shifted over time—we cannot completely rule out all alternative explanations for increasing success of songs with simpler lyrics. Future work might attempt to quantify society level time series trends in conformity or other biases linked to lyrical affect and music sampling [ 14 , 75 ], and assess whether the present findings hold when controlling for these variables as well. Future work may also use in-lab methods to explore and disentangle the possible causal mechanisms underlying the link between amount of novel song choices and success of songs with simpler lyrics. For example, transmission chain methods [ 76 ] could be employed to explore whether participants might find simpler lyrics more pleasing and memorable when there is a greater number of other song-snippets competing for attention versus when there is not.

Why have the lyrics of pop songs become simpler over time? Our findings suggest that the answer may have to do with the proliferation of new songs available to consumers. The present work represents one of the first attempts to use big data and time series methods to quantify temporal shifts in information transmission dynamics at the societal level. Future work may attempt to replicate and extend these findings into other types of complexity and other types of cultural products.

Supporting information

Funding statement.

The author(s) received no specific funding for this work.

Data Availability

• PLoS One. 2021; 16(1): e0244576.

Decision Letter 0

17 Sep 2020

PONE-D-20-20631

People prefer simpler content when there are more choices: A time series analysis of lyrical complexity in six decades of American popular music

Dear Dr. Varnum,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. 

The two reviewers provide constructive and partially overlapping comments on your framing and the analyses. I strongly encourage you to consider the additional analyses and validity checks proposed by reviewer 1 as well as addressing the conceptual questions raised by both reviewers 1 and 2.

I am also wondering whether genre and the proliferation and diversification of genres over the last century may partially be responsible for some of these effects. To what extent do these trends occur within genres or over the careers of artists/groups? Do novel genres have an advantage over more established genres? Greater attention to genres of music as well as trends for the same agent (singer/songwriter, performer) may help to address some of the conceptual issues identified by the reviewers.

Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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This is an innovative and thought provoking article. The two reviewers provide constructive and partially overlapping comments on your framing and the analyses. I strongly encourage you to consider the additional analyses and validity checks proposed by reviewer 1 as well as addressing the conceptual questions raised by both reviewers 1 and 2.

I am also wondering whether genre and the proliferation and diversification of genres over the last century may partially be responsible for some of these effects. To what extent do these trends occur within genres or over the careers of artists/groups? Do novel genres have an advantage over more established genres? Greater attention to genres of music as well as trends for the same agent (singer/songwriter, performer) may help to address some of the conceptual issues raised.

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Reviewer #1: This study explores a trend towards greater compressibility of US song lyrics, which became more repetitive over the last 6 decades. The authors test the claim that this trend is due to an increase in the variety of songs on offer. The results show that novelty in music production (henceforth "musical novelty") is a significant predictor of lyrics compressibility, even when controlling, separately, for temporal autocorrelation on the one hand, and for a host of potential confounds on the other hand.

This is an exciting and innovating study, correctly done overall, and demonstrating an intringuing and non-trivial phenomenon: song lyrics become more repetitive over time. The use of a future-oriented predictive model is particularly appreciated. If the paper merely demonstrated and explored this trend I would have no reservations about it. My main concern comes from the causal hypothesis that the study puts forward to explain the trend.

The results only partially support the authors' claims. First, because the study fails to test a set of competing explanations that seem more plausible to me than the one put forward. They are detailed below. Second, because the claim that novel music production predicts lyric compressibility above other predictors (p. 18, "the amount of novel music produced contributes to changes in average lyrical compressibility above and beyond other plausible causes") is not demonstrated or even suggested by the data. Third, no evidence is given for the contention that more compressible songs are more likely to be successful, when there is more choice (in the authors' own data or elsewhere).

1. Alternative explanations

An explanation that is alluded to in one paragraph of the discussion (p. 21) but not followed through is that song lyrics became simpler and more repetitive because listening to music became something that people did while doing other things and often without paying any particular attention (in supermarkets, elevators, bars, etc., no longer just concert halls or standing on street corners). This would readily explain why lyrics become simpler: because songs no longer have the listeners' undivided attention. This explanation is entirely distinct from the hypothesised effect of musical novelty: it is about changes in music consumption, not about changes in music production. Even so, it is coherent with the pattern of results presented here. Arguably the musical industry produced increasingly many songs because demand grew, and demand grew because people took to listening to music in circumstances where they did not use to. Changes in media of diffusion (e.g. from sheet music to radio) are an obvious and related explanation. Unless we assume that these two hypotheses are somehow equivalent or interchangeable, one cannot claim that growing musical novelty caused the observed trend without ruling out this alternative account.

One may also worry about a possible selection bias. As explained in the supplementary materials, the study selected roughly half the songs that appeared in the charts for textual analysis, due to difficulties in finding good textual data for other songs. This raises the possibility that a selection bias might explain the observed trend. It is possible that text data is better for later songs: that our documentation for 2000s hits is better than it is for 1960s hits. It is possible that songs with more less compressible lyrics are more likely to be documented, because they are more interesting, lyrics-wise, and more worthy of attention. If these two conditions obtained they would suffice to produce an apparent decrease in compressibility that would be entirely due to a preservation bias. Lyric compressibility would not actually decrease through time for unrecorded song lyrics. I am not saying that this is what happened, but this explanation is easy to rule out (just show that the proprotion of hit songs with undocumented lyrics does not change through time, or that such changes, if they occur, do not explain away the trend you observe). Relatedly, more detail on the selection of song lyrics to be analysed would be welcome: what the criteria for inclusion were, whether there was any stopping rule for data collection, etc.

2. Is novel music production a better predictor of lyric compressibility than other predictors?

The results do not establish that musical novelty is a better predictor of lyrics compressibility compared to other possible predictors studied here. Several indicators show a higher correlation with lyrics compressibility, among them (judging by Fig. 1) GDP per capita, population size, and (with an inverse correlation) residential mobility. (Although I don't know what would happen to these correlations after autocorrelation is taken into account.) To sustain the claim that musical novelty is a better predictor of lyric compressibility than other candidates, running partial correlations is not sufficient. Partial correlations merely show that the correlation between lyrics compressibility and musical novelty is robust when variable X is taken into account, but it could still be the case that variable X does better, as a predictor of lyrics compressibility, than musical novelty does.

Relatedly, it is not clear whether the correlation between lyrics complexity and musical novelty would still hold once all important confounds are controlled for *together*, and not just separately as done here. The choice of analysis that was made for this study (taking years as data points) does not allow this to be shown (too few data points), but a nested regression taking songs as data points instead of years might allow the authors to demonstrate this (with due attention being paid to multicollinearity). Alternatively, the authors could reduce all the potential confounds (all factors listed in Fig. 1 except Lyric compressibility, Music production, and Year) to one super-factor, with a PCA. Showing that the correlation between lyrics complexity and musical novelty holds when doing a partial correlation controlling for this super-factor would help make the authors' point.

3. Missing evidence of greater success for simpler songs

On p. 3–4, the study justifies the hypothesis to be tested on the grounds that people generally prefer simpler content to more complex content, especially when the choice is broad. This debatable claim is made by analogy with results in social psychology and experimental economics which in my view are not clearly relevant to the material being studied here. The similarity between a simple economic decision (e.g. a financial product that is easy to understand, as in Iyengar & Kamenica 2010) and a repetitive song, seems quite remote to me. Still, this view makes one clear prediction: more compressible songs should be more commercially successful than compressible ones, at least when there is a lot of choice. The paper seems to endorse this point but does not cite any evidence for it. It would be easy to answer this question, by comparing billboard hit songs with non-hits and controlling for various other factors.

Minor comments:

One possible confound that is (in my view) unlikely to explain the study's correlations but is easy to control for and should be ruled out, is song length: given the measurement of compressibility, I suspect song length will strongly impact compressibility, and if there is any trend in time towards shorter or longer song this might confound the observed trends.

The legend for figure 1 says that the correlations between variables are given as Kendall's tau, but I doubt it for two reasons. 1: The value given in the figure for the correlation between the Music Production index and Lyric Compressibility is .88, which does not correspond to the value reported in the main text (Kendall’s τ = .714), but does correspond to the Pearson's r correlation given in the markdown file (Pearson's r = .87723). 2. In the source code for the figure the method for the correlation is not specified (the command is cor(years, use=" " ext-link-type="uri" xlink:type="simple">pairwise.complete.obs" )). I suspect R defaults to method = "pearson" when method isn't specified. Please clarify and correct if needed.

Correlations are occasionally (exceptionally) given using Pearson's r (p. 10, also p. 14 when reporting the results for Tiokhin-Hruschka method). The authors note that this parametric correlation is inappropriate since time-series data are not normally distributed. Please remove mentions of Pearson's r or uses of it in reporting results. I recommend paying special attention to results on the Tiokhin-Hruschka method when doing so. See also the above comment regarding Fig. 1.

p. 16 AIC stands for Akaike's Information criterion (not Aikeke).

p. 20 This passage of the discussion alludes to a section of the supplementary materials that I could not find: "the aim of the present work was to understand what shapes the success of cultural products over time, rather than to use the broadest possible set of cultural products as a way to gain insight into other phenomena at the population level (see supplement for an extended discussion of this issue)."

Reviewer #2: This paper presents an analysis of why pop music in the US has become lyrically simpler over time, testing the hypothesis that the trend is driven by an expansion in the number of available song choices. This is tested by quantifying lyrical simplicity using a metric of information compressibility (LZ77 compression algorithm) over thousands of songs, and correlating this measure with estimates of the number of new songs in each year. The results support the hypothesis: large correlations between the measures.

The paper is well written and the analyses are sound and generally appropriately interpreted. The ‘multiverse’-style analysis approach is also helpful in that it provides converging different approaches. The results will be of interest to people in the psychology of music, cultural evolution, and the general public as well.

Here are a few suggestions for a revision:

(1) What songs are most popular and make it to Billboard is not unrelated to preferences, but also not that tight of a measure of people’s self directed-listening behaviours and preference for music, as is implied by the use of "preferences" throughout the paper. for instance, radio plays are influenced by advertisers, independently of people's preferences for songs. A tighter claim to make is that, as more music becomes available, simpler songs are more memorable and/or dispersible than more complicated ones. Whether and how this is related to claims in the manuscript about peoples’ music preferences changing based on Kahneman-esque heuristics being deployed due to increased cognitive load (Intro, pages 4 and 5) and/or interpreting these changes in lyrical trends as indicating changes in emotional expression (if this is what the abstract framing + discussion is implying? Eg. in “What does this tell us more broadly about how American culture has changed?”) is more up for debate, I think. This is an easy fix: just need to clarify the interpretation in the paper a bit more.

(2) The manuscript is clear that the correlational data doesn’t justify claims about causality, but it would be helpful to tighten up the areas where an interpretative claim is being made. Might the direction of causality be backwards? Songs that are simple could be easier to produce, so as artists realize they can produce simpler styles, maybe they produce more of them? There are plenty of other explanations here that would be good to discuss. For instance, maybe memorability is a big driver in what songs get a lot of radio plays, where memorability is a different aspect of music perception than preference.

(3) There may be some interesting parallels to be drawn between these results and ongoing research in how languages more generally are shaped by communicative efficiency (see for review: Gibson et al., 2019, TICS). Namely, the primary measure of simplicity of lyrics is sensitive to word length. Zipf’s law describes the frequency structure of words in a language as being related to word length (eg, Piantadosi, 2014, Psychonomic Bulletin Review), although more recent work shows that information content of words is a better predictor of word length than frequency-rank (Piantadosi et al., 2011, PNAS): in other words, more predictable words tend to be shorter. Something like Zipf's law is at work in music (see Levitin et al., 2012, PNAS; Mehr et al., 2019, Science) and so this connection with information-theoretic notions of communication would be productive. (It also fits neatly with how lyrical simplicity is quantified with LZ77).

(4) To what extent is variance in lyrical compressibility in these data mediated by the distribution of genres within the presented dataset? Electronic/dance music often has highly simple repetitive lyrics as a defining feature, for example, more so than, e.g., jazz lyrics. Perhaps one of the reasons for the popularity of electronic/dance genres within the broader popular music space may relate to this claimed attraction toward simplicity of lyrics. But the deeper point is then to ask how much of the variance in lyrical compressibility is stemming from a general trend across popular music genres and how much is contributed by relative shifts in other stylistic factors (that may be correlated with greater lyrical compressibility for additional reasons). Disentangling this is probably difficult, but I feel like it could be discussed.

For the predictions about the lyrical compressibility of future popular music, some comments about the bounds in which such extrapolation is valid/meaningful would be helpful. What does it mean for music to have an average compressibility index of ~1.225 by 2050 (as compared to the current average of ~1.1)? What are reasonable bounds of compressibility that things might plateau at?

Please check references, as at least one in-text citation was not in the end references (Steegen et al., 2016)

Mehr Krasnow 2017 is a bit of a funny citation for "music is a human universal". I think better might be Mehr et al., 2019, Science and/or the new BBS theoretical treatment ( https://doi.org/10.1017/S0140525X20000345 )

A reference about how lyrics play an important part in people’s listening habits may be helpful. For instance, this paper based on Spotify listening data would be a helpful citation: http://archives.ismir.net/ismir2018/paper/000098.pdf .

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Author response to Decision Letter 0

15 Oct 2020

Dear Dr. Fischer,

We appreciate your inviting the revision of manuscript, now entitled “Why are song lyrics becoming simpler? A time series analysis of lyrical complexity in six decades of American popular music.”

To remind you of the contribution, briefly, we explore the surprising trend that popular songs are becoming increasingly simple. We reason that the increasing production of novel songs may drive this phenomenon and test this association, finding a robust link. We situate this finding in the growing bodies of work using song lyrics to assess culture-level phenomena and work using time series analysis to understand drivers of cultural change.

We see this work as being of interest to not only to those interested in social or cultural psychology, but also those studying communication, cognitive science, and music, as well as to the lay public.

Below, we detail the changes made to this revision in line with the reviews, point-by-point, including a significant number of additional analyses. You will find critiques in plain text, with our replies italicized below. We have also highlighted major changes in the revised manuscript file in yellow for your convenience.

This is an exciting and innovating study, correctly done overall, and demonstrating an intriguing and non-trivial phenomenon.

We thank the reviewer for their enthusiasm for the work.

We have run a significant number of new analyses to address this. In particular, we comprehensively address the reviewer’s second and third points, finding that novel song production is a robust predictor of lyrical simplicity even over and above a host of other ecological and cultural predictors (see Tables 1 and 2), including in new multivariate analyses (see page 19 “Multivariate analyses”), and showing new evidence that this relationship between song success per se (as indexed by a song’s position on the Billboard chart) and novel song production is strongest in years when there are more novel songs produced (see pages 19-21 “Exploratory song-level analyses”).

The reviewer also raised two competing hypotheses:

An explanation that is alluded to in one paragraph of the discussion (p. 21) but not followed through is that song lyrics became simpler and more repetitive because listening to music became something that people did while doing other things and often without paying any particular attention (in supermarkets, elevators, bars, etc., no longer just concert halls or standing on street corners). This would readily explain why lyrics become simpler: because songs no longer have the listeners' undivided attention. This explanation is entirely distinct from the hypothesised effect of musical novelty: it is about changes in music consumption, not about changes in music production.

We now address this point at even greater length in the discssion section (see page 25 first full paragraph), noting that, in particular, technology-mediated changes may influence music consumption practices. However, respectfully disagree that changes in listener attention are likely to cause the shift in lyrical simplicity seen here; for example, people have listened to music in their cars for decades, portable music players have been available for decades, and music has been featured as the background noise in various entertainment establishments for decades. Further, although an interesting avenue for future research, we feel it is beyond the scope of the present work to assess music listening patterns for reasons described on page 25 first full paragraph)

One may also worry about a possible selection bias. As explained in the supplementary materials, the study selected roughly half the songs that appeared in the charts for textual analysis, due to difficulties in finding good textual data for other songs. This raises the possibility that a selection bias might explain the observed trend. It is possible that text data is better for later songs: that our documentation for 2000s hits is better than it is for 1960s hits. It is possible that songs with more less compressible lyrics are more likely to be documented, because they are more interesting, lyrics-wise, and more worthy of attention.

In order to address this point we conducted analyses that controlled for percentage of charting songs for which lyrics could be successfully scraped (see page 18-19 “Robustness analyses: Controlling for percentage of scraped songs”). Our key relationship held controlling for this possibility.

Relatedly, more detail on the selection of song lyrics to be analysed would be welcome: what the criteria for inclusion were, whether there was any stopping rule for data collection, etc.

Additional details regarding the processing of song lyrics can be found on pages 2-3 of the Supporting Information.

Is novel music production a better predictor of lyric compressibility than other predictors?... The results do not establish that musical novelty is a better predictor of lyrics compressibility compared to other possible predictors studied here. Several indicators show a higher correlation with lyrics compressibility, among them (judging by Fig. 1) GDP per capita, population size, and (with an inverse correlation) residential mobility. (Although I don't know what would happen to these correlations after autocorrelation is taken into account.) To sustain the claim that musical novelty is a better predictor of lyric compressibility than other candidates, running partial correlations is not sufficient. Partial correlations merely show that the correlation between lyrics compressibility and musical novelty is robust when variable X is taken into account, but it could still be the case that variable X does better, as a predictor of lyrics compressibility, than musical novelty does.

We understand the reviewer’s concern, however we note that we do not claim that musical novelty is the best predictor of average lyrical compressibility. That said, we believe that new analyses in which we look at detrended relationships between all putative predictors and average lyrical compressibility suggest that it is one of only three significant predictors, and the only one for which we frankly had an a priori hypothesis when we began the work. We attempt no interpretation of the negative relationship between conservatism and compressibility, and we do talk briefly about the negative relationship between pathogens and compressibility, which we suggest should be followed up on in the future. That said, again our focus was on testing our a priori hypotheses about ONE possible driver of growing lyrical simplicity, hence we focus on this in the present manuscript.

We are grateful to the reviewer for this suggestion. Our new multivariate analyses follow these suggestions (p.19) and find that our key effect holds. Taken together we believe we have a great deal of evidence for the robustness of our key finding and we are grateful to the reviewer for helping strengthen the rigor of the manuscript.

Missing evidence of greater success for simpler songs On p. 3–4, the study justifies the hypothesis to be tested on the grounds that people generally prefer simpler content to more complex content, especially when the choice is broad. This debatable claim is made by analogy with results in social psychology and experimental economics which in my view are not clearly relevant to the material being studied here. The similarity between a simple economic decision (e.g. a financial product that is easy to understand, as in Iyengar Kamenica 2010) and a repetitive song, seems quite remote to me. Still, this view makes one clear prediction: more compressible songs should be more commercially successful than compressible ones, at least when there is a lot of choice. The paper seems to endorse this point but does not cite any evidence for it. It would be easy to answer this question, by comparing billboard hit songs with non-hits and controlling for various other factors.

Great point! We’ve taken this advice to heart (see pages 19-20, “Exploratory Song-level analyses,”) and we do find empirical support for this claim. Namely, among Billboard charting songs, those that are more compressible are more successful. Further this relationship is stronger in years in which more novel songs are produced. We thank the reviewer for suggesting this and we believe again that the rigor of the manuscript and the fit between evidence and the rationale in the introduction has been enhanced as a result.

Minor comments

- One possible confound that is (in my view) unlikely to explain the study's correlations but is easy to control for and should be ruled out, is song length: given the measurement of compressibility, I suspect song length will strongly impact compressibility, and if there is any trend in time towards shorter or longer song this might confound the observed trends.

We now address this possibility in the discussion section. Based on empirical findings regarding song length of Billboard charting songs, we do not feel that this alternative explanation can explain our observations. See below (from page 26):

“Another possibility is that the length of songs may have changed over time affecting average lyrical complexity. Thus, perhaps song lyrics are more compressible by virtue of songs becoming shorter. However, a recent analysis of songs entering the Billboard charts over the course of its history suggests, in fact, that the average song on the charts in the late 2010’s was somewhat longer than those in the 1950’s and 1960’s, and similar in recent years to levels observed in the 1970’s (Bannister, 2017). Thus, this alternative explanation cannot account for the trends observed in the present analyses.”

- The legend for figure 1 says that the correlations between variables are given as Kendall's tau, but I doubt it for two reasons. 1: The value given in the figure for the correlation between the Music Production index and Lyric Compressibility is .88, which does not correspond to the value reported in the main text (Kendall’s τ = .714), but does correspond to the Pearson's r correlation given in the markdown file (Pearson's r = .87723). 2. In the source code for the figure the method for the correlation is not specified (the command is cor(years, use=" pairwise.complete.obs ")). I suspect R defaults to method = "pearson" when method isn't specified. Please clarify and correct if needed.

We are grateful to the reviewer for catching this error. This has now been corrected in Table S1 which reports kendall’s tau’s instead of pearson’s r’s.

We understand the reviwer’s concern here. However we note that the Tiokhin-Hruschka procedure can only produce corrected significance thresholds for Pearon’s r at present. We have opted to leave these results in in the spirit of a multiverse approach. Importantly, this is only one approach used to account for autocorrelation, and importantly we get converging inferences using these different approaches. However, if the editor wishes, we are happy to move this section the supplement or to OSF as a supporting file.

Again, we are grateful to the reviewer for catching the error. It is now corrected.

We discuss this issue on page 27-8 of the revised manuscript and on pages 3-4 of the revised supplement. We hope this discussion is sufficient.

What songs are most popular and make it to Billboard is not unrelated to preferences, but also not that tight of a measure of people’s self directed-listening behaviours and preference for music, as is implied by the use of "preferences" throughout the paper. for instance, radio plays are influenced by advertisers, independently of people's preferences for songs. A tighter claim to make is that, as more music becomes available, simpler songs are more memorable and/or dispersible than more complicated ones. Whether and how this is related to claims in the manuscript about peoples’ music preferences changing based on Kahneman-esque heuristics being deployed due to increased cognitive load (Intro, pages 4 and 5) and/or interpreting these changes in lyrical trends as indicating changes in emotional expression (if this is what the abstract framing + discussion is implying? Eg. in “What does this tell us more broadly about how American culture has changed?”) is more up for debate, I think. This is an easy fix: just need to clarify the interpretation in the paper a bit more.

We have addressed this issue in line with the reviewer’s helpful comment; namely we clarify the interpretation in the present revision.

The manuscript is clear that the correlational data doesn’t justify claims about causality, but it would be helpful to tighten up the areas where an interpretative claim is being made. Might the direction of causality be backwards? Songs that are simple could be easier to produce, so as artists realize they can produce simpler styles, maybe they produce more of them? There are plenty of other explanations here that would be good to discuss. For instance, maybe memorability is a big driver in what songs get a lot of radio plays, where memorability is a different aspect of music perception than preference.

We agree that causal inference is inherently limited when analyzing this type of data. We have tried throughout the revised manuscript to be cautious in terms of causal and mechanistic claims, especially in the revised discussion section. We have also added several new analyses (see replies to reviewer 1 for details) that we hope do strengthen the inferences made, although again stopping short of claiming to show causality.

There may be some interesting parallels to be drawn between these results and ongoing research in how languages more generally are shaped by communicative efficiency (see for review: Gibson et al., 2019, TICS). Namely, the primary measure of simplicity of lyrics is sensitive to word length.

Zipf’s law describes the frequency structure of words in a language as being related to word length (eg, Piantadosi, 2014, Psychonomic Bulletin Review), although more recent work shows that information content of words is a better predictor of word length than frequency-rank (Piantadosi et al., 2011, PNAS): in other words, more predictable words tend to be shorter. Something like Zipf's law is at work in music (see Levitin et al., 2012, PNAS; Mehr et al., 2019, Science) and so this connection with information-theoretic notions of communication would be productive. (It also fits neatly with how lyrical simplicity is quantified with LZ77).

We thank the reviewer for pointing out this interesting parallel, which we now treat at some length in the Discussion (pages 23-24). We additionally link the present data and this work to another area of literature dealing with cultural evolution and communicative efficiency:

Minor comments: For the predictions about the lyrical compressibility of future popular music, some comments about the bounds in which such extrapolation is valid/meaningful would be helpful. What does it mean for music to have an average compressibility index of ~1.225 by 2050 (as compared to the current average of ~1.1)? What are reasonable bounds of compressibility that things might plateau at?

We are grateful for this insightful set of suggestions. We have now added the following description which we hope helps guide the reader’s intuitions (pg. 7) : “A score of 0 means no compression was possible (e.g. if the input were random noise), a score of 1 means a 50% reduction in size, a score of 2 means a 75% reduction, and so on.”

Further, there is a theoretical upper limit on compressibility score for any given length. The most repetitive possible song of length n would be a single letter repeated n times, and it would have a score of (log n) - 2. But this is so far from the reality of the data as to not be very interesting.

Please check references, as a least one in-text citation was not in the end references (Steegen et al., 2016).

We have now double checked the reference list and it should now match all in text citations. Thanks to the reviewer for catching this!

We agree and have switched the citation to Mehr et al., 2019.

AE Decision Letter

These are good points. We agree that genre would be an interesting avenue for future exploration and we now include an extended discussion of this issue in the revised discussion section (page 26). In terms of tracking the course of an individual artist’s output, this would also be an intriguing possibility, however we would be dealing with small N’s for most and potential confounds having to do with the aging process (i.e. executive function decline with age) that would be difficult to disentangle from broader cultural forces. We hope that with the additional analyses, revisions, and explication now provided that the reviewers points are largely addressed even though we did not opt to attempt analyses by genre or within artist. We hope that you will agree that the new analyses reported in the revision are in fact sufficient to all most major concerns.

In sum, we believe that we have addressed all major points raised by reviewers, and that the present revision is suitable for publication in PLOS ONE. We are grateful to the two reviewers and to yourself for the insightful feedback and critique. We believe the manuscript has improved tremendously as a result. We look forward to your reply.

Decision Letter 1

14 Dec 2020

Why are song lyrics becoming simpler? A time series analysis of lyrical complexity in six decades of American popular music

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Acceptance letter

18 Dec 2020

Dear Dr. Varnum:

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Dr. Ronald Fischer

song lyrics in essays

<p>has anyone ever used song lyrics to describe or relate to their life experiences and wrote it in their essay?</p>

<p>Better keep your ideas to yourself if you want to be original. :-)</p>

<p>Maybe you could put a line or two at the top or bottom of an essay, as a quote or a title of sorts.</p>

<p>Otherwise, probably a bad idea.</p>

<p>Well, that might be original…or very MySpace-y. Either or. Be careful with the lyrics you choose.</p>

<p>If you decide to go this route, make SURE you credit them!! You do NOT want to look like you’re plagiarizing!</p>

<p>yeah…also, don’t just sporadically put them. WHile thesemay be your favorite lyrics, your admissions officer may not have even heard of the songs!</p>

<p>The idea itself is in no way bad, whatsoever. It doesn’t matter if the adcoms have heard the song, it doesn’t necessarily matter where in your essay you place the lyrics either. Just do what works.</p>

<p>Its not a bad idea, just make sure that it fits into the essay and that you’re not just hiding behind someone else’s words. Make sure your essay has your voice, and that it’s strong, before introducing someone else’s.</p>

<p>If you want to do an essay like that, just make sure that it flows and the lyrics are only aiding your own words, not taking away. Also, don’t try putting more than two lines of the song in any one place as anything more than that is usually excessive.</p>

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Good Songs To Analyze For English Class

[ad_1] Good Songs To Analyze For English Class in 2024

Music has always been a powerful form of expression, and analyzing songs in an English class can provide a unique and engaging way for students to explore various themes, literary devices, and cultural contexts. As we enter the year 2024, here are some good songs to consider for analysis in an English class, along with eight interesting facts about each song.

1. “Blinding Lights” by The Weeknd:

– Released in 2019, “Blinding Lights” became a global hit in 2020, making it an excellent choice for analyzing contemporary music.

– The song’s lyrics and music video draw inspiration from the 1980s, making it a great opportunity to explore themes of nostalgia and retro culture.

– “Blinding Lights” features the literary device of repetition, with the chorus being repeated several times throughout the song.

– The Weeknd’s vocal range and emotive delivery make this song a great example for discussing the use of tone and mood in music.

– The song’s popularity and critical acclaim make it a relevant topic for discussing the impact of music in today’s society.

2. “Bad Guy” by Billie Eilish:

– Released in 2019, “Bad Guy” showcases Billie Eilish’s unique style and lyrical prowess, making it an intriguing choice for analysis.

– The song plays with themes of power dynamics and subverting expectations, providing an opportunity to explore gender roles and societal norms.

– “Bad Guy” employs various literary devices, such as irony and sarcasm, to convey its message.

– The song’s minimalist production and Eilish’s whisper-like vocals create a haunting atmosphere, allowing for discussions on the use of sound in music.

– Billie Eilish’s rise to stardom and the cultural impact of her music can be explored in relation to “Bad Guy.”

3. “Formation” by Beyoncé:

– Released in 2016, “Formation” became an anthem for Black empowerment, making it a significant song to analyze in terms of social and political commentary.

– The lyrics of “Formation” address issues of racism, feminism, and cultural identity, providing ample material for discussion.

– The song’s music video is rich in symbolism and references to African-American history, allowing for analysis of visual storytelling in music.

– “Formation” showcases Beyoncé’s powerful vocals and her ability to use her platform to address important issues, making it a relevant topic for exploring the role of artists as activists.

– The controversy surrounding the release of “Formation” and its impact on pop culture can be explored within the context of analyzing this song.

4. “Old Town Road” by Lil Nas X:

– Released in 2019, “Old Town Road” broke records and blended genres, making it an interesting choice for analysis.

– The song’s lyrics play with themes of identity and genre conventions, sparking discussions on artistic authenticity and cultural appropriation.

– “Old Town Road” incorporates elements of both country and hip-hop music, providing an opportunity to explore the evolution of musical genres and their cultural significance.

– The song’s viral success and the debate it sparked within the music industry can be examined in relation to the power of social media and online communities.

– “Old Town Road” also addresses issues of perseverance and self-expression, making it a compelling topic for exploring personal narratives in music.

5. “Imagine” by John Lennon:

– Released in 1971, “Imagine” remains a timeless classic that continues to resonate with listeners, making it a valuable song for analysis in any English class.

– The song’s lyrics promote themes of peace, unity, and the power of imagination, providing ample material for discussing utopian ideals and social activism.

– “Imagine” utilizes vivid imagery and metaphors, allowing for exploration of poetic devices within song lyrics.

– The song’s message and its relevance in today’s world can be discussed in relation to ongoing global conflicts and the pursuit of social justice.

– John Lennon’s role as a cultural icon and his impact on music and activism make “Imagine” a significant song to analyze.

6. “Royals” by Lorde:

– Released in 2013, “Royals” became a breakout hit for Lorde, making it an excellent choice to explore the perspective of a young artist navigating fame and societal expectations.

– The song’s lyrics critique materialism and the excesses of popular culture, providing opportunities for discussions on consumerism and social class.

– “Royals” showcases Lorde’s distinctive vocal style and her ability to craft thought-provoking lyrics, making it a great example for analyzing poetic techniques in music.

– The song’s success at such a young age can be discussed in terms of the pressures faced by young artists in the music industry.

– “Royals” also offers an interesting contrast to other popular songs of its time, making it a valuable topic for exploring musical trends and cultural shifts.

7. “Hallelujah” by Leonard Cohen:

– Originally released in 1984, “Hallelujah” has been covered by numerous artists and continues to be a beloved song, making it a timeless choice for analysis.

– The song’s complex and poetic lyrics lend themselves to discussions on themes of love, spirituality, and the human experience.

– “Hallelujah” features a variety of literary devices, such as biblical allusions and powerful imagery, providing ample material for analysis.

– The song’s enduring popularity and the different interpretations it has garnered over the years can be examined in relation to the concept of artistic legacy.

– Leonard Cohen’s role as a revered singer-songwriter and the impact of his music can be discussed within the context of analyzing “Hallelujah.”

8. “This Land Is Your Land” by Woody Guthrie:

– Written in 1940, “This Land Is Your Land” has become an American folk classic that addresses themes of inclusivity, equality, and social justice, making it a valuable song for analysis in an English class.

– The song’s lyrics explore the vast landscapes of America and the idea of shared ownership, providing opportunities to discuss environmentalism and the concept of belonging.

– “This Land Is Your Land” showcases Guthrie’s storytelling abilities and his use of vivid imagery, making it a great example for analyzing narrative techniques in music.

– The song’s historical context and its place within the American folk music tradition can be examined in relation to broader discussions on cultural heritage.

– Woody Guthrie’s role as a protest singer and the impact of his music on social movements can be explored within the context of analyzing “This Land Is Your Land.”

In conclusion, analyzing songs in an English class can offer students a valuable opportunity to explore various themes, literary devices, and cultural contexts. The songs mentioned above, such as “Blinding Lights,” “Bad Guy,” “Formation,” “Old Town Road,” “Imagine,” “Royals,” “Hallelujah,” and “This Land Is Your Land,” provide a diverse range of topics for analysis. By delving into the lyrics, musical elements, and societal impact of these songs, students can deepen their understanding of the power of music as a form of artistic expression.

15 Common Questions and Answers:

1. What is the significance of analyzing songs in an English class?

Analyzing songs allows students to explore themes, literary devices, and cultural contexts in a unique and engaging way.

2. Why is “Blinding Lights” by The Weeknd a good choice for analysis?

“Blinding Lights” is a popular contemporary song that incorporates nostalgia and repetition as literary devices.

3. What themes can be explored in “Bad Guy” by Billie Eilish?

“Bad Guy” addresses power dynamics, gender roles, and societal expectations.

4. How does “Formation” by Beyoncé contribute to social and political commentary?

“Formation” addresses racism, feminism, and cultural identity within the African-American community.

5. What makes “Old Town Road” by Lil Nas X an interesting song to analyze?

“Old Town Road” blends genres, explores themes of identity, and sparked debates on cultural appropriation.

6. Why is “Imagine” by John Lennon considered a timeless classic?

“Imagine” promotes themes of peace, unity, and imagination, which remain relevant in today’s world.

7. What societal critique does “Royals” by Lorde offer?

“Royals” criticizes materialism and excesses in popular culture, allowing for discussions on consumerism and social class.

8. How does “Hallelujah” by Leonard Cohen utilize literary devices?

“Hallelujah” features biblical allusions, vivid imagery, and poetic techniques that deepen its meaning.

9. Why is “This Land Is Your Land” by Woody Guthrie a valuable song for analysis?

“This Land Is Your Land” addresses inclusivity, equality, and social justice, making it a significant song in American folk tradition.

10. How can analyzing these songs enhance students’ understanding of the power of music?

Analyzing songs helps students explore the impact of music on society, cultural shifts, and personal narratives.

11. What is the role of repetition in “Blinding Lights” by The Weeknd?

Repetition emphasizes the song’s catchy chorus and contributes to its overall impact on listeners.

12. How does Billie Eilish use irony in “Bad Guy”?

Billie Eilish employs irony to subvert expectations and challenge societal norms.

13. What visual storytelling elements are present in the music video for “Formation” by Beyoncé?

The music video of “Formation” contains rich symbolism and references to African-American history.

14. How does “Old Town Road” by Lil Nas X challenge genre conventions?

“Old Town Road” blends elements of country and hip-hop, challenging traditional genre boundaries.

15. Why has “Imagine” by John Lennon remained relevant over time?

“Imagine” continues to resonate with listeners due to its timeless message of peace and unity.

Final Thoughts:

Analyzing songs in an English class not only allows students to explore various themes, literary devices, and cultural contexts but also deepens their understanding of the power of music as a form of artistic expression. Songs such as “Blinding Lights,” “Bad Guy,” “Formation,” “Old Town Road,” “Imagine,” “Royals,” “Hallelujah,” and “This Land Is Your Land” provide rich material for analysis and discussions on social, political, and personal narratives. By delving into the lyrics, musical elements, and societal impact of these songs, students can develop critical thinking skills and gain a deeper appreciation for the role of music in our lives. [ad_2]

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The song remains the same —

Song lyrics are getting more repetitive, angrier, an analysis of 50 years of popular music lyrics reveals a number of trends..

Elizabeth Rayne - Apr 15, 2024 4:29 pm UTC

From ‘80s new wave to ‘90s grunge to the latest pop single, music has changed a lot over the decades. Those changes have come not only in terms of sound, though; lyrics have also evolved as time has passed.

So what has changed about the lyrics we can’t get out of our heads? After analyzing 12,000 English-language pop, rock, rap, R&B, and country songs released between 1970 and 2020, researcher Eva Zangerle of Innsbruck University and her team have found that lyrics have been getting simpler and more repetitive over time. This trend is especially evident in rap and rock, but it applies to other genres as well. Another thing Zangerle’s team discovered is that lyrics tend to be more personal and emotionally charged now than they were over 50 years ago.

Know the words…

“Just as literature can be considered a portrayal of society, lyrics also provide a reflection of a society’s shifting norms, emotions, and values over time,” the researchers wrote in a study recently published in Scientific Reports.

That's why Zangerle created a dataset to find out the different ways in which lyrics have changed. She and her colleagues used the virtual music encyclopedia Genius, which also provides release year and genre information. From the lyric dataset she created, the team pulled data having to do with the structure, language, emotion, and complexity of songs. Five genres—pop, rock, rap, R&B, and country—were chosen because they are genres with the most lyrics that were popular on streaming platform last.fm .

There were two types of analyses done on the music. The first looked for the lyrical trends that were most prevalent for each release year, while the second went deeper into online views of lyrics, characteristics of lyrics (such as emotion), and release year. The researchers obtained the play count from last.fm and the lyrics view count from Genius.

How often people view the lyrics is unexpectedly important. Unlike play counts of songs, this stat shows how important lyrics are despite the popularity (or lack thereof) of the song or genre.

…and the meaning

What can lyrics tell us about different genres and eras? Results for the first analysis showed that certain characteristics are most important across genres, including repeated lines, choruses, and emotional language. The genres in which emotion was most important were country and R&B.

Repeated lines increased over the decades in all genres analyzed, and later lyrics contain more choruses than earlier ones. These increases are further proof that songs have become simpler and more repetitive since the ‘70s.

Lyrics were also more personal and angrier across all genres studied. Personal lyrics were identified by the number of personal pronouns, which especially increased in rap and pop, while rock and R&B saw moderate increases and country stayed nearly the same. Anger and other negative emotions (as expressed through words associated with these emotions) also increased across genres. Rap had the highest increase here, especially in anger, while country showed the lowest increase. Positive emotions decreased in pop and rock, while they increased somewhat in rap.

When looking at the results from the second analysis, Zangerle noticed that lyric views were higher for older rock songs than newer ones, and vice versa for country, which had lower view counts for older songs and higher view counts for new songs. This means that the popularity of country lyrics has increased over time in comparison to rock. Listening count had no relationship to this, meaning interest in the sound of a song was not related to interest in its lyrics.

Through the decades, it seems that music has gotten simpler, more repetitive, and more emotional—especially angrier—and more personal. The study didn’t look into what events and societal changes might have influenced this trend, but the researchers still had some sociological insights. They think pop is all about record sales and what's hot from one moment to the next, while the preference for older rock songs shows that the main audience of rock is middle-class and against commercialism. Emotionally charged words could also convey feelings toward shifts in society.

The researchers “believe that the role of lyrics has been understudied and that our results can be used to further study and monitor cultural artifacts and shifts in society,” the study said.

Scientific Reports, 2024.  DOI: 10.1038/s41598-024-55742-x

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Taylor Swift Doesn’t Hide the Travis Kelce References in ‘The Alchemy’

This Tortured Poets Department track is an anthem for the Tayvis era.

Regardless of the song’s ultimate target, there’s no question Swift’s aware her sports references will draw immediate attention to Kelce, and to the ever-growing phenomenon that is the Tayvis era. “The Alchemy” is an anthem of sorts, a no-holds-barred embrace of Swift’s latest chapter. Even her less obvious lyrics speak to a sense of playfulness: “I circled you on a map” could be a wink at claims Swift put Kelce “on the map.” Or “those blokes warm the benches,” a barb at her British exes, including both Joe Alwyn and Matty Healy. “Child’s play back at school”? Perhaps a callback to her own earlier catalogue, in which she referenced high-school jock-and-cheerleader stereotypes in songs like “You Belong With Me.”

Swift isn’t exactly kissing and telling. But if everyone’s already paying attention to every move she and Kelce make together, the singer might as well enjoy her wordplay. You can read the full lyrics to “The Alchemy” ahead:

This happens once every few lifetimes These chemicals hit me like a white wine

What if I told you I’m back? The hospital was a drag, Worst sleep that I ever had I circled you on a map I haven’t come around in so long But I’m coming back so strong

So when I touch down Call the amateurs and cut ’em from the team Ditch the clowns, get the crown, Baby I’m the one to beat ’Cause the sign on your heart Said it’s still reserved for me Honestly, who are we to fight the alchemy?

Hey you, what if I told you we’re cool? That child’s play back in school Is forgiven under my rule I haven’t come around in so long But I’m making a comeback to where I belong

These blokes warm the benches We’ve been on a winning streak He jokes that it’s heroin but this time with an ‘E’ ’Cause the sign on your heart Said it’s still reserved for me Honestly, who are we to fight the alchemy?

Shirts off and your friends lift you up over their heads Beer sticking to the floor, Cheers chanted ’cause they said There was no chance tryna be the greatest in the league Where’s the trophy? He just comes running over to me

Touch down Call the amateurs and cut ’em from the team Ditch the clowns, get the crown, Baby I’m the one to beat ’Cause the sign on your heart Said it’s still reserved for me Honestly, who are we to fight the alchemy?

Go Even Deeper on Taylor Swift

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Taylor Swift’s 30 Things I Learned Before Turning 30

Read Swift’s candid essay for ELLE about the life lessons she learned before hitting that milestone year.

Taylor Swift and Joe Alwyn’s Complete Relationship Timeline

Swift spent six years dating Alwyn. Revisit the history that Tortured Poets is expected to explore.

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A Brief Guide to Who’s Who on Taylor Swift’s ‘Tortured Poets’

Ex-boyfriends may be alluded to. Travis Kelce, too, fans believe. And some actual poets.

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By Madison Malone Kircher

When Taylor Swift released “The Tortured Poets Department,” on Friday at midnight, her fan base quickly got to work decoding the album, looking for layers of meaning and insight into Ms. Swift’s life. Of course, that includes the pop singer’s romantic history.

Like many of her past works, the songs on this album — which features over a dozen additional tracks as part of an extended album called “The Tortured Poets Department: The Anthology” — are laden with names and references, many of which appear to be to real people from Ms. Swift’s universe and the literary canon. At least two poets, Dylan Thomas and Patti Smith, are mentioned.

Here’s a look at some of those characters.

Matty Healy

Plenty of lines from “Tortured Poets” have fans guessing that certain songs — including “The Smallest Man Who Ever Lived,” “The Black Dog” and “Down Bad” — may be about Matty Healy , the frontman for the 1975 who was spotted out and about with Taylor on several occasions last spring. One clue Swifties are latching on to: On the “The Black Dog,” Ms. Swift refers to the band the Starting Line. Mr. Healy covered one of the band’s songs while he was touring last spring. And then there is the much-discussed reference to a person Ms. Swift describes as a “tattooed golden retriever" on the album’s title track. Mr. Healy seems to fit the bill, according to her fans.

Travis Kelce

Ms. Swift’s fans have been floating the notion that the many sports references in the track “The Alchemy” allude to the football player Travis Kelce , the singer’s current boyfriend. “So when I / Touch down, call the amateurs and cut ’em from the team / Ditch the clowns, get the crown, baby, I’m the one to beat," she sings in the chorus. “Where’s the trophy? / He just comes running over to me,” she adds in the bridge. But there is some debate, with some fans noting that her use of the term “blokes” would seem to imply the song is not about an American. (A winking line about “heroin but this time with an E” has some guessing the song is about Mr. Healy, who has previously spoken about his drug use.)

Ms. Swift and the actor Joe Alwyn broke up last year after a lengthy relationship. In the lead-up to the release of “Tortured Poets,” many fans believed this new album would process the end of that relationship. (Mr. Alwyn said in a 2022 interview that he was in a group text chat with the actors Paul Mescal and Andrew Scott called “ The Tortured Man Club .” Some fans believe Ms. Swift was nodding to this name with her latest album title.) There is some speculation that Track 5, “So Long, London,” is about Mr. Alwyn, who is British.

Jack Antonoff

A longtime collaborator of Ms. Swift’s, Jack Antonoff, who is credited as a producer on many of the new album’s songs, appears to get a lyrical shout out on the album’s title track.

The musician Lucy Dacus also appears on that same track. (In addition to her work as a solo artist, Ms. Dacus is a member of the supergroup boygenius, who surprised fans with a performance during a stop on Ms. Swift’s Eras tour last year.) “Sometimes, I wonder if you’re gonna screw this up with me / But you told Lucy you’d kill yourself if I ever leave / And I had said that to Jack about you, so I felt seen,” Ms. Swift sings.

Kim Kardashian

Ms. Swift often leaves clues for fans by capitalizing seemingly random letters in words which, when strung together, spell a different word. In the case of this album, the song “thanK you aIMee,” seems to reveal the name Kim. (Ms. Swift and Kim Kardashian have a long and unfriendly history .)

In Greek mythology, Cassandra is given the gift of prophecy by Apollo, but is cursed such that no one will ever believe her. On a song with the same name as the goddess, Ms. Swift sings, “So they killed Cassandra first / ’Cause she feared the worst / And tried to tell the town / So they filled my cell with snakes, I regret to say / Do you believe me now?” Snake emojis have also played a key role in the feud between Ms. Swift and Ms. Kardashian.

Charlie Puth

The singer-songwriter Charlie Puth gets a name drop on the title track: “You smoked then ate seven bars of chocolate / We declared Charlie Puth should be a bigger artist.” Mr. Puth, through a representative, declined to comment.

The song “Peter” appears to refer to the storybook character Peter Pan. “You said you were gonna grow up / Then said you were gonna come find me,” Ms. Swift sings. She has made similar allusions in the past, including a line about “Peter losing Wendy” on her song “cardigan” in 2020.

Patti Smith

The American singer, songwriter, poet and author Patti Smith gets a name check on the title track in a line about New York’s iconic Chelsea Hotel , where she once lived. Ms. Smith has been hailed as the “ punk poet laureate .”

Dylan Thomas

The Welsh poet, known for works like “Do not go gentle into that good night,” is also mentioned along with Ms. Smith. “You’re not Dylan Thomas / I’m not Patti Smith / This ain’t the Chelsea Hotel / We’re modern idiots,” Ms. Swift sings. Thomas, who was also a resident at the Chelsea, is famous for his work as a neo-Romantic poet. (Ms. Swift has an older song, from her album “1989,” titled “New Romantics.”)

Clara Bow, an actress from the silent film era known as the first “it girl,” has an entire song dedicated to her on “Tortured Poets.” In 1927, Bow starred in a film titled “It” and became a national sex symbol before leaving the industry. Fans have pointed out that Ms. Swift’s thinly drawn eyebrows in a video teasing a new music video to accompany the song “Fortnight” bear a striking similarity to Ms. Bow’s.

Stevie Nicks

Stevie Nicks is named on the song “Clara Bow.” Ms. Nicks has said that Ms. Swift’s song “You’re on Your Own Kid” reminds her of Christine McVie, her Fleetwood Mac bandmate who died in 2022 . “You look like Stevie Nicks / In ’75, the hair and lips,” Ms. Swift sings in the song. (Ms. Nicks also wrote an original poem that accompanies a special vinyl edition of “Tortured Poets.”)

Madison Malone Kircher is a Times reporter covering internet culture. More about Madison Malone Kircher

Inside the World of Taylor Swift

A Triumph at the Grammys: Taylor Swift made history  by winning her fourth album of the year at the 2024 edition of the awards, an event that saw women take many of the top awards .

‘The T ortured Poets Department’: Poets reacted to Swift’s new album name , weighing in on the pertinent question: What do the tortured poets think ?  

In the Public Eye: The budding romance between Swift and the football player Travis Kelce created a monocultural vortex that reached its apex  at the Super Bowl in Las Vegas. Ahead of kickoff, we revisited some key moments in their relationship .

Politics (Taylor’s Version): After months of anticipation, Swift made her first foray into the 2024 election for Super Tuesday with a bipartisan message on Instagram . The singer, who some believe has enough influence  to affect the result of the election , has yet to endorse a presidential candidate.

Conspiracy Theories: In recent months, conspiracy theories about Swift and her relationship with Kelce have proliferated , largely driven by supporters of former President Donald Trump . The pop star's fans are shaking them off .