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Key Research Findings on Influencer Marketing [Insights]

by Jacob Goldenberg, Andreas Lanz, Daniel Shapira, and Florian Stahl

The influencer endorsement market more than doubled from 2019 to 2021, growing from $6.5 billion to $13.8 billion ( Statista 2021 ). User-generated content networks like Instagram, LinkedIn, SoundCloud, Twitter, and YouTube fueled the growth as they transformed the customer targeting, acquisition, and retention process.

Influencers and their followings provide firms unique access to potential customers difficult to reach through channels like online banner advertisements. As a result, companies have found selecting powerful influencers to seed customer targets can drive marketing success ( Haenlein and Libai 2017 ).

But which influencers should firms target to find potential customers? Significant literature suggests high-status influencers with large followings are effective (e.g., Hinz et al. 2011 ). Such macro-influencers, or “hubs” ( Goldenberg et al. 2009 ), boost information dissemination in user-generated content networks and drive product adoption. More recently, researchers and practitioners have recognized the value of micro-influencers with only a few followers (e.g., Haenlein et al. 2020 ). Sometimes the generation gap between an influencer and potential customers leads to misalignment (Clegg et al. 2022).

Several recent publications offer important and actionable insights for individuals and firms attempting to seed customers in the evolving social media landscape.

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Selecting Influencers

Individual and corporate social network users can use their own profiles to shape their follower base through outbound activities. By targeting influencers with follows, private messages, likes, and reposts, they can trigger notifications in the influencers’ timelines and possibly elicit follow-backs. The strategy, especially relevant for small- and medium-sized enterprises, requires no monetary budget and, when successful, represents an unpaid endorsement from the influencer.

Outbound activities can trigger direct returns via follow-backs from influencers and indirect returns via follow-backs from influencers’ followers. Indirect returns rely on influencers reposting content.

Lanz et al. (2019) find that network users do not generally benefit from soliciting unpaid endorsements from macro-influencers with large followings because they are orders of magnitude less responsive than micro-influencers. Direct returns are therefore unlikely and risky. When macro-influencers do respond, the researchers find the indirect returns from their followers do not compensate for the high risk. Lanz and colleagues offer the first empirical evidence for micro-influencers’ effectiveness, finding them to be six times more effective than macro-influencers for growing a follower base of potential customers within two years.

The idea also applies to paid endorsements, as macro-influencers may be unreceptive to requests, regardless of compensation. According to Lanz and colleagues’ 2019 work, endorsements depend on the status difference between the solicitor and influencer. Beyond status difference, the solicitor for a paid endorsement must realize that an endorsement may positively bias the influencer’s content while decreasing its persuasiveness due to the affiliation ( Pei and Mayzlin 2021 ). For paid endorsements, it is important to specify the affiliation.

When selecting influencers, Valsesia, Proserpio, and Nunes (2020) find following fewer other users signals autonomy and enhances perceived influence. The researchers suggest that macro-influencers typically follow few others, while micro-influencers have more balanced follower-to-followee ratios.

Todri, Adamopoulos, and Andrews (2021) demonstrate that users may form a sense of social identity based on their physical location. Even in online environments geographical proximity matters for social influence.

Firms should also consider network overlap when selecting influencers. Overlap may occur among common followees, common followers, or common mutual followers. Peng et al. (2018) find return likelihood increases with network overlap. Although the researchers find that all forms of network overlap positively affect reposting (i.e., indirect returns), common followers are more important than common mutual followers. In a simulation study, the authors show that a 20% increase in network overlap is associated with a 13% decrease in influencer activation time.

Strengthening Follower Bases

Ansari et al. (2018) find that outbound activities can generate significant long-term impacts via follower base growth and content consumption, with follower base connectedness being critical—and offering considerable predictive power. Individuals and firms should therefore supplement their outbound efforts with activities to increase connectedness, such as additional opportunities for followers to interact on- or offline. The researchers focus on musicians and suggest concerts and fan gatherings as examples.

Chen, van der Lans, and Phan (2017) demonstrate that assuming a binary network structure, where users simply follow each other or not (e.g., Ansari et al. 2018 ; Lanz et al. 2019 ), can be misleading. The researchers therefore develop a multinetwork approach for activating influencers by inferring network connection weights based on features like recency and interaction intensity, as well as dissemination process. In an empirical application, they demonstrate relationship duration and private message exchanges generate a multinetwork extending beyond connections alone.

What value does growing a follower base of potential customers to support wide content dissemination deliver? Based on a Facebook field experiment in which they consider an incentive-based health and wellness program allowing customers to accumulate points for offline behaviors like exercising, Mochon et al. (2017) find that business page likes (i.e., followers) can translate into changes in offline behaviors, including purchases. Specifically, using social media platform functionality to acquire likes translates into a 8% greater influence on offline customer behaviors. (For more on the value of Facebook likes, see Colicev (2021) .)

For unpaid social network endorsements, the most basic form of influencer marketing, firms can capitalize on outbound activities like follows, private messages, likes, and reposts. However, activating micro-influencers can be more effective than approaching macro-influencers.

Firms must also consider geographical proximity as well as the number of followees and network overlap when selecting influencers for customer seeding. Moreover, marketers must increase connectedness among their own follower base to achieve long-term impacts, meaning they must carefully integrate each new follower into their existing egocentric network, as there is more to a connection than simply a follow.

Author Bios

Jacob Goldenberg is Professor of Marketing at Reichman University, Herzliya, Israel, and a Visiting Professor at Columbia Business School, New York, New York.

Andreas Lanz is Assistant Professor of Marketing at HEC Paris, Jouy-en-Josas, France.

Daniel Shapira is Senior Lecturer in Marketing at Ben-Gurion University, Beer Sheva, Israel, and a Permanent Adjunct Research Faculty at the University of Mannheim, Mannheim, Germany.

Florian Stahl is Professor of Marketing at the University of Mannheim, Mannheim, Germany.

Goldenberg, Jacob, Andreas Lanz, Daniel Shapira, and Florian Stahl (2021), “Influencer Marketing,” Impact at JMR , (February), Available at: https://www.ama.org/2022/02/16/the-research-behind-influencer-marketing/

Ansari, Asim, Florian Stahl, Mark Heitmann, and Lucas Bremer (2018), “Building a Social Network for Success,” Journal of Marketing Research , 55(3): 321–38. https://doi.org/10.1509/jmr.12.0417

Chen, Xi, Ralf Van der Lans, and Tuan Q. Phan (2017), “Uncovering the Importance of Relationship Characteristics in Social Networks: Implications for Seeding Strategies,” Journal of Marketing , 54(2): 187–201. https://doi.org/10.1509/jmr.12.0511

Clegg, Melanie, Reto Hofstetter, Lea Schindler, Olivia Deubelbeiss, Andreas Lanz, Martin Faltl, and Torsten Tomczak (2022), “Bridging the Generational Divide,” Harvard Business Review , Magazine Jan/Feb.

Colicev, Anatoli (2021), “The Real Value of Facebook Likes,” Impact at JMR , January. https://www.ama.org/2021/01/26/the-real-value-of-facebook-likes/

Goldenberg, Jacob, Sangman Han, Donald R. Lehmann, and Jae Weon Hong (2019), “The Role of Hubs in the Adoption Process,” Journal of Marketing , 73(2): 1–13. https://doi.org/10.1509/jmkg.73.2.1

Haenlein, Michael, Ertan Anadol, Tyler Farnsworth, Harry Hugo, Jess Hunichen, and Diana Welte (2020), “Navigating the New Era of Influencer Marketing: How to be Successful on Instagram, TikTok, & Co.,” California Management Review , 63(1): 5–25. https://doi.org/10.1177/0008125620958166

Haenlein, Michael, and Barak Libai (2017), “Seeding, Referral, and Recommendation: Creating Profitable Word-of-Mouth Programs,” California Management Review , 59(2): 68–91. https://doi.org/10.1177/0008125617697943

Hinz, Oliver, Bernd Skiera, Christian Barrot, and Jan U. Becker (2011), “Seeding Strategies for Viral Marketing: An Empirical Comparison,” Journal of Marketing , 75(6): 55–71. https://doi.org/10.1509/jm.10.0088

Lanz, Andreas, Jacob Goldenberg, Daniel Shapira, and Florian Stahl (2019), “Climb or Jump: Status-Based Seeding in User-Generated Content Networks,” Journal of Marketing Research , 56(3): 361–78. https://doi.org/10.1177/0022243718824081

Mochon, Daniel, Karen Johnson, Janet Schwartz, and Dan Ariely (2017), “What Are Likes Worth? A Facebook Page Field Experiment,” Journal of Marketing Research , 54(2): 306–17. https://doi.org/10.1509/jmr.15.0409

Pei, Amy, and Dina Mayzlin (2021), “Influencing Social Media Influencers Through Affiliation,” Marketing Science , Article in Advance. https://doi.org/10.1287/mksc.2021.1322

Peng, Jing, Ashish Agarwal, Kartik Hosanagar, and Raghuram Iyengar (2018), “Network Overlap and Content Sharing on Social Media Platforms,” Journal of Marketing Research , 55(4): 571–85. https://doi.org/10.1509/jmr.14.0643

Statista Research Department (2021), “Influencer marketing market size worldwide from 2016 to 2021,” Statista.com , Aug. 12. https://www.statista.com/statistics/1092819/global-influencer-market-size/

Todri, Vilma, Panagiotis Adamopoulos, and Michelle Andrews (2021), “Is Distance Really Dead in the Online World? The Moderating Role of Geographical Distance on the Effectiveness of Electronic Word-of-Mouth,” Journal of Marketing , forthcoming. https://doi.org/10.1177/00222429211034414

Valsesia, Francesca, Davide Proserpio, and Joseph C. Nunes (2020), “The Positive Effect of Not Following Others on Social Media,” Journal of Marketing Research , 57(6): 1,152–68. https://doi.org/10.1177/0022243720915467

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• Published: 27 January 2024

Shall brands create their own virtual influencers? A comprehensive study of 33 virtual influencers on Instagram

• Zheng Shen   ORCID: orcid.org/0000-0003-2348-5189 1  

Humanities and Social Sciences Communications volume  11 , Article number:  177 ( 2024 ) Cite this article

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• Business and management
• Cultural and media studies
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Increasing customer-brand engagement on social media has been a focus of brand success for many years. Recently, virtual influencers have gained popularity as a new way for brands to increase customer engagement, but there has been limited analysis of this new phenomenon. As such, by investigating 33 virtual influencers on Instagram, this study explored whether brands should create or collaborate with virtual influencers and how they can increase customer-brand engagement. The findings reveal that non-branded virtual influencers are more engaged than branded virtual influencers. Also, virtual influencers’ communication strategies to increase customer-brand engagement were further discussed in the study to develop a typology of virtual influencers. Thus, this study fills a theoretical gap in the limited analysis of virtual influencers in customer-brand engagement, and suggests that brands collaborate with virtual influencers rather than creating their own virtual influencers in practice.

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Introduction.

Increasing the engagement between brands and customers on social media has been a focus of brand attention for many years. Previous studies have shown that social media allows brands to build network-based online communities that stimulate customer engagement by enabling customers to develop their social identities and satisfy social needs (Vernuccio et al., 2016 ). Existing literature further suggests that customer-brand engagement has a significant impact on brand loyalty, customer perceptions of brand advertisements, willingness to share, and purchase intentions (Hollebeek and Macky, 2019 ; Izogo and Mpinganjira, 2020 ; Wang et al., 2022 ). As more and more virtual influencers emerge, brands are increasing their partnerships with them to promote their products and even engage in developing their own virtual influencers due to their popularity. Global AI spending is expected to grow from $50 billion in 2020 to more than $110 billion by 2024, and they are the latest genre to soar (Lou et al., 2022 ). For many, virtual influencers are seen as the future of marketing, advertising and commerce (Robinson, 2020 ).

More recently, academic research has begun to explore virtual influencers and their application in marketing (Vrontis et al., 2021 ; Sands et al., 2022 ). Most of these prior studies analyzed virtual influencers from an influencer marketing perspective, noting that the importance of virtual influencers in marketing (de Brito Silva et al., 2022 ). In contrast to human influencers, scholars have begun to examine how social media users perceive the authenticity and credibility of virtual influencers, and the impact on marketing and advertising effectiveness (Balaban and Szambolics 2022 ; Lou et al., 2022 ). However, in the pertinent literature on virtual influencers, there is a limited number of studies on virtual influencers in terms of customer-brand engagement, in particular previous studies have not addressed the analysis of differences in customer responses and engagement with brands based on the characteristics of different types of virtual influencers (Mrad et al., 2022 ). In other words, previous studies have noted that virtual influencers offer the potential for a new field of user engagement (Arsenyan and Mirowska, 2021 ), but existing research has argued that this aspect has been neglected by academics and marketers, not least because virtual influencers are controlled by brands, which may limit their reach and engagement (de Brito Silva et al., 2022 ).

As such, the existing literature remains questionable as to whether users perceive virtual influencers as credible, or even whether the aforementioned elements are important for consumers who come into contact with such influencers. The research question raised in this study is whether brands should create or collaborate with virtual influencers in order to increase customer-brand engagement. This study argues that brands can collaborate with non-brand sponsored virtual influencers rather than the time-consuming and labor-intensive process of developing their own virtual influencers, which can be more effective in increasing customer engagement. This study innovates and contributes to the existing literature by providing a typology of customer-brand engagement conducted by virtual influencers and their communication strategies on Instagram from both customer and brand perspectives. Due to the limited analysis of virtual influencers currently available, particularly since the extant literature mainly uses case studies, this study further provides a comprehensive understanding of virtual influencers’ customer engagement by topologizing 33 Instagram-verified virtual influencers and their communication strategies. Consequently, this study provides theoretical and practical insights for brand practitioners to increase customer-brand engagement and capitalize on virtual influencers.

Theoretical background

Customer-brand engagement on social media.

Strengthening customer-brand engagement is of growing theoretical and managerial importance in the marketing literature (García-de-Frutos and Estrella-Ramón, 2021 ; Gligor and Bozkurt, 2021 ; Ji et al., 2022 ). Existing literature considers the importance of customer-brand engagement in marketing in terms of its potential predictive power of customer behavior and brand performance (Pansari and Kumar, 2017 ; Santini et al., 2020 ). Pansari and Kumar ( 2017 ) argue that customer-brand engagement forms a relationship when customers form satisfying relationships based on trust, commitment, and emotional bonds. Santini et al. ( 2020 ) argue that customer-brand engagement directly affects brand performance and indirectly affects brand performance through behavioral intention and WOM.

Early studies of customer-brand engagement failed to address recent technological innovations that continue to open up new possibilities for customer-brand interactions (Paruthi and Kaur, 2017 ). As technology has evolved, customers have increasingly accessed social media platforms as a means of expressing their opinions and interacting with brands, which has led to brands using social media to identify and interact with engaged customers for specialized marketing campaigns (Baldus et al., 2015 ). Thus, Hollebeek et al. ( 2014 ) in their study of social media environments defined customer-brand engagement as cognitive, emotional, and behavioral activities related to a brand that are positively evaluated by customers during or in relation to customer or brand interactions. Kircova et al. ( 2018 ) further explain that customer-brand engagement on social media platforms consists of how customers how they use, share, and talk about brand-related content.

Extant literature has found a strong relationship between brand image on social media and customer perceptions of the brand (Liu et al., 2020 ). Hajli et al. ( 2017 ) state that brand strategies can be developed through social media as social interactions between customers and brands in online communities improve relationship quality and brand loyalty. Kamboj et al. ( 2018 ) support that social media significantly affects customer engagement, which in turn affects brand trust and loyalty, ultimately leading to having a positive brand image and purchase intention. Based on the importance of the above issues, scholars are increasingly interested in exploring the determinants that drive customer-brand engagement. Determinants identified in the existing literature include product quality (Purnawirawan et al., 2012 ), customer reviews (Borah and Tellis, 2016 ), and effective content (Hanlon, 2019 ).

The aforementioned studies reveal the following limitations of the existing literature. For one thing, previous studies have focused on customer engagement, aiming to increase customer engagement in online communities through electronic word-of-mouth in product reviews (Purnawirawan et al., 2012 ). As explained by Santini et al. ( 2020 ), previous studies have discussed customer engagement from a customer contribution perspective rather than a customer-brand engagement perspective. Specifically, by examining product reviews, previous studies have concentrated on conceptualizing and measuring customer engagement in terms of factors such as intrinsic motivations, psychological states, and customer activities (Harmeling et al., 2017 ). However, these customer intrinsic motivation factors do not take into account the fact that customer engagement on social media may be influenced by such extrinsic motivations as brand activities on social media and getting likes and comments on social content (Santini et al., 2020 ; Shen, 2023a ). Therefore, this study provides a comprehensive understanding of customer-brand engagement with virtual influencers on social media by examining brand posts and customer responses from both brand and customer perspectives, rather than a single investigation of customer factors.

For another, there is limited analysis on customer engagement with brands on social media platforms. Chahal and Rani ( 2017 ) argue that while previous studies have explored customer-brand engagement on social media, analysis of social media itself as a determinant of customer-brand engagement has been limited in previous studies. In addition, current research has rarely analyzed customer-brand engagement conducted by virtual influencers (Arsenyan and Mirowska, 2021 ; Sands et al., 2022 ; Stein et al., 2022 ), which is further explained in the next section.

The rise of virtual influencers and virtual interactivity

With the development of technology, current scholars have proposed virtual influencer research (Lee et al., 2022 ; Thomas-Francois and Somogyi, 2022 ; Ahn et al., 2023 ). Virtual influencers are defined as computer-generated influencers or artificial intelligence influencers that have a wide following on social media (Conti et al., 2022 ). They can be human-like or non-human-like, and are visually presented as interactive, real-time rendered entities (Sands et al., 2022 ). Park et al. ( 2021 ) further state that virtual influencers are fictionalized modern versions of branded characters or mannequins in store windows that suddenly become more realistic and authentic. From the above definitions, virtual influencers are influential, social, and interactive, and seem to have similar characteristics and effects as social media influencers in general. Lil Miquela, has over 6.2 million followers on Instagram, 2.7 million followers on YouTube, 1.4 million followers on Twitter, and 7 million followers on TikTok, and is recognized as one of the most influential people on the Internet by Time . Thanks to their influence, a significant number of virtual influencers have already been involved in campaigns for global brands, such as Hatsune Miku for Domino’s Pizza in 2013, Noonoouri for Dior in 2018, Lil Miquela for Samsung in 2019, and Imma for IKEA Japan in 2020. It is estimated that virtual influencers can earn up to $11 million per year from brand campaigns, much higher than the average income of social media influencers (Business Insider, 2021 ).

The lure and influence of virtual influencers for financial gain has attracted the attention of academics, who have begun to explore virtual influencers and their applications in marketing, advertising, and other fields. Previous studies have focused on the authenticity and credibility of virtual influencers compared to real human influencers on social media (Mrad et al., 2022 ; Lou et al., 2022 ). Mrad et al. ( 2022 ) indicate that the congruence between virtual influencers and their perfect images and lives makes it possible for consumers to recognize them as real influencers. However, Lou et al. ( 2022 ) find that virtual influencers are effective in shaping brand image and increasing brand awareness, but they lack the persuasive power to motivate purchase intentions due to their lack of authenticity, low similarity to followers, and weak parasocial relationship with followers. Lou et al. further explain that Mori’s Uncanny Valley Theory (1790) can help us understand this result, as many other studies have shown that accurate portraits of virtual influencers lead to negative consumer effects (Schwind et al., 2018 ).

In contrast, different academic voices have argued that not all types of human-likeness manipulation elicit the uncanny valley (Kätsyri et al., 2015 ). Block and Lovegrove ( 2021 ) point out that virtual influencers like Lil Miquela create familiar or unfamiliar experiences through the fearful and obsessive uncanny valley storyworlds, which propel the virtual influencers’ persuasive power among their followers. Overall, these inconsistent findings highlight the important role that the uncontrollability of virtual influencers plays in customer response and engagement, and as Miao et al. ( 2022 ) suggest, anthropomorphic appearance is an important feature of virtual influencers because people interact differently with what they perceive to be more human-like. Namely, the reasons for customers’ acceptance of the uncontrollability that characterizes virtual influencers have not been explored in depth, and despite the uncanny valley effect, virtual influencers still have a large and engaged following (Block and Lovegrove, 2021 ). While prior research has typically focused on followers’ perceptions of virtual influencers’ appearances (Jang and Yoh, 2020 ), there has been a lack of research on other factors that may influence their uncontrollability, such as virtual influencers’ behaviors, characteristics, and personalities (Lou et al., 2022 ). This motivates the present study to provide a more nuanced interpretation of the uncontrollability of virtual influencers.

From an engagement perspective, existing literature reveals that virtual influencers are not only interactive, but also offer a new way of user engagement (Arsenyan and Mirowska, 2021 ). According to the Virtual Influencers Survey 2022, 58% of respondents follow at least one virtual influencer, and have purchased a product promoted by a virtual influencer (Forbes, 2022 ). Research has found that people project themselves into anthropomorphic interactions with machines through social presence (Potdevin et al., 2020 ). Moreover, it has been found that engaging with human agents through digital media fulfills people’s need for personal identity, distraction, social relationships, and autonomy (Hanus and Fox 2015; Gaines, 2019 ). Using Miquela as a case study, Block and Lovegrove ( 2021 ) emphasize that the discordant and uncanny human qualities of virtual influencers make them appealing to post-millennial audiences. De Brito Silva et al. ( 2022 ) reveal that avatars are effective advocates in marketing who generate engagement through a range of strategies from humanization to robotization. When it comes to branding, however, some previous studies have shown different results, i.e., virtual influencers can reduce customer engagement while generating positive branding benefits (Thomas and Fowler, 2021 ; Sands et al., 2022 ). Lou et al. ( 2022 ) explain that this is due to the lack of authenticity, their low similarity to followers and weak parasocial relationships with followers, and thus lack the persuasive power to motivate customers’ purchase intentions. Inconsistent findings suggest that customer responses to virtual influencers in the context of branding remain ambiguous (Miao et al., 2022 ; Mrad et al., 2022 ). Therefore, more research should be further conducted to clarify customer engagement with virtual influencers’ branding on social media.

By reviewing these recent studies on virtual influencers, studies on virtual influencer engagement are still in their infancy, especially in terms of customer-brand engagement conducted by virtual influencers (Miao et al., 2022 ; de Brito Silva et al., 2022 ). Table 1 shows that recent studies on virtual influencers have focused on comparing virtual influencers with human influencers in terms of authenticity and credibility. Although one of the research focuses of de Brito Silva et al.’s analysis ( 2022 ) is on virtual influencer engagement, the study still focuses on the authenticity of virtual influencers rather than on virtual influencers’ customer-brand relationships and marketing strategies. In addition, these studies focus on the case of Lil Miquela rather than virtual influencers in general. With the rapid rise of virtual influencers, of which there are now more than 200, and the breadth of their influence, there is a need to fully understand the significance of virtual influencers for brands, customers, and their relationships.

Recently, brands have even started creating their own virtual influencers. For instance, KFC virtualized Colonel Sanders as a younger and healthier person. However, the creation and development of virtual influencers has also led to a significant amount of funding for brands. Spark Capital, for example, made a $125 million round of investment in Brud, a startup that created the world’s first virtual influencer, Lil Miquela (The Verge, 2019 ). Therefore, is creating and developing virtual influencers for brands worth the huge effort and money? It is difficult to make a judgment without fully understanding the customer-brand effect of virtual influencers. In summary, this study categorizes 33 Instagram virtual influencers into branded and non-branded groups and compares their customer-brand engagement and communication strategies according to their different categories, posing the following research questions that innovate and contribute to the existing literature:

(1) What is the level of customer-brand engagement for different categories of branded and non-branded virtual influencers?

(2) How can customer-brand engagement of virtual influencers be increased?

(3) Should brands create their own virtual influencers? Or collaborate?

Data collection

To address the research questions, virtual influencers on Instagram were selected for data collection. Instagram was chosen as the social media platform for this study because it is one of the fastest growing social networking sites and the most used platform by influencers (Pineda et al., 2020 ). In addition, Instagram is reported to be the most popular platform for consumers to follow virtual influencers in 2022 (Statista Research Department, 2023 ). According to Casaló et al. ( 2021 ), followers of committed online communities are more likely to interact on Instagram. Existing literature on virtual influencers also selects Instagram to understand virtual influencers (de Brito Silva et al., 2022 ). Therefore, this platform is particularly suitable for analyzing the interactions of virtual influencers with customers and brands.

Subsequently, selected virtual influencers were drawn from a list of 35 virtual influencers verified by Instagram in 2022 (see https://www.virtualhumans.org/article/instagram-has-verified-35-virtual-influencers ). For sampling purposes, virtual influencers who had suspended their activities (Casas Bahias, Knox Frost, Kizuna AI, Ryan, FN Meka, CodeMiko, Squeaky and Roy, APOKI, Chill Pill, and Hatsune Miku) were removed. Hence, the remaining 25 virtual influencers were included in the study. Based on the branded and non-branded categorization of virtual influencers in VirtualHumans.org, 8 of them are branded virtual influencers and 17 non-branded virtual influencers. VirtualHumans.org provides the best source of information about virtual influencers, and recent research has proven that its branded and non-branded categorization can be used to study virtual influencers (Conti et al., 2022 ). As stated in the first research question, this study sought to compare the level of customer-brand engagement between branded and non-branded virtual influencers; therefore, based on the VirtualHumans.org’s categorization of all listed branded and non-branded virtual influencers (see https://www.virtualhumans.org/article/these-brands-are-creating-humans-you-can-too , and https://www.virtualhumans.org/t/brand ), an additional six branded virtual influencers (Barbie, Pete Zaroll, Emily, Maya Gram, Diego Martinez, and Mavrello Ballovic) and two non-branded virtual influencers (K/DA and WarNymph) were added to increase the number of branded virtual influencers in this study, and to supplement the sample of branded and non-branded virtual influencers according to VirtualHumans.org’s categorization. Finally, a sample of 33 virtual influencers on Instagram were selected for this study, including 14 branded virtual influencers and 19 non-branded virtual influencers (see Table 2 for details).

Data analysis and coded variables

To collect data, we manually collected each virtual influencer’s Instagram posts (up to December 2022). These posts are primary data collected from the official Instagram accounts of virtual influencers. Since these posts are available online and open to the public, anyone can see them without having to ask the brand’s permission in advance. Therefore, we reviewed a total of 23,260 posts using a mixed method of content analysis and descriptive statistics, as in previous studies (Creswell, 2014 ; de Brito Silva et al., 2022 ).

Specifically, we first collected descriptive statistics on the number of likes, comments, and followers, and then analyzed customer-brand engagement via SPSS. Existing literature supports the use of the number of likes and comments as key indicators of customer-brand engagement on social media (Unnava and Aravindakshan 2021 ). Likes are interpreted as customers accepting the perception of posts and holding positive attitudes towards brand images (Antonopoulos et al., 2015 ). Comments can be viewed as a communication tool to help marketers understand their customers ahead of time, as customers need to expend more effort to express their thoughts, attitudes and feelings when commenting than simply clicking the like button (Lev-On and Steinfeld, 2015 ). Previous studies have shown that user engagement in the form of likes and comments on social media positively affects offline customer behavior (Mochon et al., 2017 ; Lee et al., 2018 ). For this reason, gaining customer engagement (e.g., likes and comments) has become almost an obsession for many brands and marketing practitioners. They are considered important tools for customizing a brand’s online message and communicating effectively with customers (Shen 2021 ). Consistent with the existing literature mentioned above, this study identifies them as coded variables for calculating customer-brand engagement for virtual influencers on Instagram. That is to say, we refer to Unnava and Aravindakshan’s ( 2021 ) calculation of average customer-brand engagement in terms of average number of likes and comments versus number of followers.

Subsequently, with reference to Shahbaznezhad et al.’s ( 2021 ) study, highly engaged posts and comments were further categorized and content-analyzed for each virtual influencer based on the rate of engagement between the customer and the brand. Categorizing influencers is an important perspective to effectively utilize influencers, as social media influencers can be more targeted to serve specific interest groups and communities (Hanlon and Tuten, 2022 ). Previous studies have classified social media influencers based on their follower numbers and motivation (Campbell and Farrell, 2020 ). According to Kozinets et al. ( 2010 ), market-based messages and their acceptance by the target audience are influenced by character narratives, forums, communal orientation, and promotional characteristics. Character narratives refer to the personality traits of the communicator and the personal stories associated with particular expressed character types. Forums refer to communication venues, such as specific social networking sites. Communal norms vary by community size, interests, lifestyles, and shared history, and these norms govern the expression, dissemination, and reception of information. Finally, promotional characteristics include product types, brand equity, brand objectives, hard-sell nature, and the humor of campaigns.

Accordingly, this study builds on Kozinets et al.’s ( 2010 ) study by categorizing virtual influencers through content analysis with DiVoMiner. DiVoMiner is a well-known global platform for processing textual data using content analysis methods. A specific tutorial on how to use DiVoMiner for content analysis can be found on its official website ( https://www.divominer.com/en/ ). In terms of coding variables for content analysis, this study builds on the research of Kozinets et al.’s ( 2010 ) by focusing on four variables, namely character narratives, forums, promotional characteristics, and community reactions. Specifically, character narratives refer to virtual influencers’ characteristics and the way they are narrated in the posts. Moreover, forum focuses on virtual influencers’ communication strategies on Instagram, while community reactions refer to customer-brand engagement in likes and comments. Also, promotional characteristics include product types, brand equity, brand objectives, humor of campaigns, and relevant marketing strategies. As a result, this study conceptualized a typology of virtual influencers and analyzed their engagement with customers and brands. The research design is demonstrated below (see Fig. 1 ).

The research design.

Authenticity and categories of virtual influencers

Generally speaking, current virtual influencers consist of branded and non-branded influencers. Branded virtual influencers are created by brands, initially to promote their brand. A prime example is Lu of Magalu, who first came to life promoting iBlogTV on behalf of Magazine Luiza. Other examples include Good Advice Cupcake, created by Buzzfeed, and Guggimon and Janky, created by vinyl-toy company Superplastic (see Table 2 ). Non-branded virtual influencers, like real influencers, have a wide following on social media and sometimes work with brands as brand ambassadors. For example, Imma, a star from Tokyo, debuted as an international fashion model in 2018. Other popular professions are pop stars (e.g., Lil Miquela, K/DA, and Teflon Sega), fashion icons (e.g., Noonoouri, Shudu Gram, and Plusticboy), and social media influencers (e.g., Nobody Sausage, Ronald F. Blawko, and Ilona), and like real influencers, these professions are more likely to garner large fan followings and brand partnerships. Sometimes, the boundaries of professions blur with popularity, similar to the way human influencers live their lives. For example, Rozy Oh is a popular virtual influencer and model from South Korea. She is known for her expressive face and fashion sense. She has recently ventured into music and is about to release her debut album.

After classifying virtual influencers, branded and non-branded virtual influencers can be further categorized into animalistic, 2D animated, doll-like, and humanoid virtual influencers based on their authenticity and human-likeness. An animalistic virtual influencer refers to a virtual influencer whose face or body looks like an animal. For example, Guggimon is a virtual rabbit and Janky is a virtual cat that is Guggimon’s best friend. The virtual influencers of 2D animation are animated characters from well-known cartoons and comics such as Minnie Mouse, Any Malu, and Teflon Sega. In the case of doll-like virtual influencers, some are more like real human, such as Qai Qai and Noonoouri, but it’s still easy to tell the difference between real and virtual humans. Others are more doll-like than human, such as Nobody Sausage and Mavrello Ballovic. Finally, humanoid virtual influencers tend to have a high degree of humanization, which sometimes makes it difficult to judge their authenticity (see Fig. 2 ).

Typical examples of virtual influencer category.

Customer-brand engagement by category

Table 3 shows, from high to low, the customer-brand engagement of different categories of virtual influencers. According to Unnava and Aravindakshan ( 2021 ), the average customer-brand engagement is calculated by comparing the average number of likes and comments with the number of followers. The results show that Nobody Sausage has the highest customer-brand engagement (30.74%), while the top 6 types and categories with the highest customer-brand engagement are all non-branded and doll-like virtual influencers. Moreover, Lu of Magalu has the lowest customer-brand engagement (0.07%), and the bottom six low customer-brand engagement types are all branded virtual influencers. Since the overall customer-brand engagement is higher for non-branded virtual influencers, the results indicate that non-branded virtual influencers have higher customer-brand engagement than branded virtual influencers.

However, the results do not reveal which specific categories of virtual influencers have higher customer-brand engagement among branded or non-branded virtual influencers, as some doll-like virtual influencers (e.g., Nobody Sausage, K/DA, Seraphine Song, Yameii Online, and Warnypmh) have higher engagement rates, while other doll-like virtual influencers (e.g., Noonoouri, Qai Qai, Barbie and Emily) have considerably lower engagement rates. Furthermore, the previously mentioned doll-like virtual influencers have higher engagement rates than humanoid virtual influencers (e.g., Bermuda, Ion Göttlich, Imma and Ronald F. Blawko), which in turn have higher engagement rates than doll-like virtual influencers (e.g., Mavrello Ballovic, Ilona, and Noonoouri). The results suggest that virtual influencers’ authenticity and humanization do not affect their customer-brand engagement, further demonstrating no support for the Uncanny Valley.

By analyzing virtual influencers’ posts and relevant comments, this study summarized their character narratives, forums, promotional characteristics, and community reactions based on Kozinets et al.’s ( 2010 ) study mentioned above, and categorized them into four types of virtual influencers, including virtual storyteller, social connector, product demonstrator, and brand assistant. Due to word count constraints, each type is described in detail below with representative examples (see Fig. 3 for details).

The typology of virtual influencers.

Virtual storyteller: fantasy but honest expression and life

This type of virtual influencer acts like a real human, telling and sharing their life with their followers. For example, a virtual influencer can fall in love. In 2021, Plusticboy announced on Instagram that he was in a relationship with another virtual influencer, Ria. In the caption, he described his feelings for her and how they developed into a loving couple (see Fig. 4 ). This post received 5909 likes and 69 comments. Since then, he has posted about their love story from time to time in his posts. Among the posts, there was a high level of engagement with posts related to their romantic relationship. In this way, these two virtual influencers have come together to create a new storyline that unites their respective communities of followers. They often use their relationships to develop their characters and drive their narratives by leaving their followers wondering what’s next for the couple.

Example of virtual storyteller.

In addition to romantic relationships, these virtual influencers are involved in other relationships, such as kinship and friendship. For example, Plusticboy and Imma’s sibling relationship is reflected in their narratives of traveling, visiting exhibitions, and hanging out with their virtual influencer friends like Ella on Instagram. That is to say, virtual influencers use Instagram to communicate in a form similar to fictional diaries and novels in which stories are told in the first person. While these stories resemble fantasy, virtual influencers try to make them more real and relatable, which contributes to their easy acceptance by followers. This is also evidenced by the comments. When commenting on Plusticboy and Ria’s romance, followers are happy for them and accept this fictional story by “Congrats to both of you! You look great together”, “I really love to see you guys being a couple now”, “Kiss Kiss!”, and “I had this feeling before that you two are couple, congratulations”. Regarding commercial concealment, these virtual influencers minimize or avoid mentioning brand campaigns and their involvement. They focus on sharing their life stories rather than brand promotion.

Social connector: mocking and seeking social connections

This type of virtual influencers seeks social connections by making funny posts on Instagram. Nobody Sausage, for example, creates content with groovy dance moves in Instagram videos targeting Gen-Z and Millennials. According to Nobody Sausage, its goal is to “bring happiness, love, and high vibration to other people on a daily basis. Especially in these difficult times, bringing the energy up is so important—giving high vibration of love to each other”. Correspondingly, these hilarious posts not only bring joy to followers, but also resonate with them culturally and contextually, ultimately leading to high engagement. Figure 5 , for example, shows a video about four scenes: the first scene is a happy blow-drying of hair; the second scene is a tired and depressed mood; the third scene is a joyful jumping in the shower; and the fourth scene is a moody meal. The resonance and positive response from followers is reflected in their comments: “Winter in Canada be like”, “NYC too”, “That’s why I can’t do the roommate thing…always different moods under same roof”, “Haha so true”, and “That is exactly the daily routine of Gemini like me”.

Example of social connector.

In terms of branding, the focus of such non-branded virtual influencers is on seeking social connections and increasing their influence among their followers rather than brand campaigns. However, as their influence grows, brands are beginning to invite them to collaborate. For instance, Hugo Boss partnered with Nobody Sausage for its Spring/Summer 2022 campaign as the brand looked to inspire new and younger target groups and convert them into fans. Nobody Sausage posted a photo on Instagram wearing a Hugo Boss hoodie and tagging the brand and the campaign. Fans immediately responded with applause, adoration and fiery emojis, totaling 29,928 likes and 238 comments. The high level of engagement on these posts indicates that followers are very supportive of occasional brand campaign due to the previous resonance and fan base.

Product demonstrator: product exhibitionism to meet marketing intent

This type of virtual influencers typically posts photos of themselves wearing branded products that directly feature the brand to fulfill marketing intent. Daisy Yoox and Noonoouri, for instance, post their outfit of the day in each Instagram post, and explicitly mention or tag the brand name or product (see Fig. 6 ). The image on the left is from Daisy Yoox and is captioned “8 by ESSENTIALS sweatshirt transforms into four closet classics! Check out all the variations you can match with this #8byYOOX staple piece on #YOOX!” The animation in the post shows Daisy wearing sweatshirt in different colors for different effects. The post mentions and tags its brand YOOX several times to inform its customers. Similarly, the image on the right is from Noonoouri and is captioned “Gianni FOREVER @donatella_versace @versace #Versace”. The post directly points out the brand of the dress—Versace. That is to say, the focus of these posts is to highlight the brand message and give customers a strong brand image. For this reason, the posts are concise to highlight the brand identity. The brand name in the form of capital letters, mentions and hashtags is highly visible.

Examples of product demonstrator.

Regarding customer-brand engagement, these posts have relatively low engagement. The most frequent response is likes with very few comments. For example, the Daisy Yoox post above received 675 likes and 5 comments. As mentioned by Reijmersdal et al. ( 2016 ), consumers turn to resisting the persuasion of sponsor blogs because of their obvious marketing intentions. In other words, customers tend to be free to choose what they like, and refuse to be manipulated by influencers when they find strong and obvious marketing intentions in social media posts. When they recognize marketing messages (e.g., brand and product names) in posts, customers feel that their freedom of choice is threatened, which further causes followers to resist these posts. For this reason, virtual influencers of product demonstrators have relatively low levels of customer-brand engagement due to their obvious commercial purpose.

Brand assistant: implicitly assisting and embracing commercialization

Unlike product demonstrators, virtual influencers of brand assistants hide their commercial purpose in different daily activities such as sports, travel, useful advice, and charity events. For example, Mar.ia is a virtual influencer with a loving heart. Since its inception in 2020, she has been pursuing social justice while promoting plant-based health, gender equality, and environmental causes. In addition, Shudu Gram, another virtual influencer, takes time away from location shoots to advocate for the needs of the growing virtual influencer community. Some have praised her for advocating for the inclusion of black beauty and diversity in fashion as a black woman, while others feel that models of color are being robbed of jobs. She also partners with eco-friendly brands and their products. For instance, she has partnered with Hyundai Motor Company to launch Re:Style, an evolving eco-friendly lifestyle and fashion platform that utilizes eco-friendly recycled materials from Hundai’s manufacturing process into seat belts. Moreover, Ion Göttlich’s and Diego Martinez’s Instagram posts about gravel bikes and healthy cycling evoke 15–30 K likes (see Fig. 7 ). Regarding customer reactions, this type of virtual influencers has a relatively high level of customer-brand engagement due to their typically positive daily activities. These positive daily activities help to build a favorable image of virtual influencers. Under the influence of a favorable image, customers are likely to accept Instagram posts about brand campaigns because they have a good image and are consistent with the brand image, even if they imply brand messages.

Examples of brand assistant.

Theoretical and managerial implications

In summary, this study makes a three-fold contribution. First, this study extends the existing literature on customer-brand engagement with virtual influencers. Existing literature has limited analysis of customer-brand engagement on social media platforms (Shen, 2023b ). In particular, current research rarely analyzes the impact of virtual influencers on customer-brand engagement (Sands et al., 2022 ). This study examined the customer-brand engagement of 33 virtual influencers on Instagram, and found that non-branded virtual influencers were more engaged than brand virtual influencers. According to Ho et al. ( 2015 ), “consumers today are not susceptible to one-way advertising. Besides, consumers have more autonomy and product options, so the advertising effectiveness of most advertisements is unsatisfactory” (p. 359). The findings support previous research that brand posts result in less engagement with customers on social media (Shen, 2021 ), regardless of whether the posts are made by real influencers or virtual influencers. Therefore, this study concludes that virtual influencers can have different impacts on brands and customers depending on the explicit or implicit marketing intentions they display in their posts, and disagrees with previous studies that all virtual influencers produce positive brand benefits and are effective in building brand image and increasing brand awareness (Thomas and Fowler, 2021 , Lou et al., 2022 ).

Second, this study provides a further comprehensive understanding of virtual influencer marketing on social media. Research on virtual influencer marketing is still in its infancy (de Brito Silva et al., 2022 ). Existing literature focuses on the case of Lil Miquela rather than virtual influencers in general (Mrad et al., 2022 ). Among these studies, few have analyzed the characteristics of virtual influencers that engage followers, and their customers’ reactions (Thomas and Fowler, 2021 ; Miao et al., 2022 ). This study develops a typology of virtual influencers grounded on Kozinets et al. ( 2010 ), and categorized them into virtual storytellers, social connectors, product demonstrators, and brand assistants. It complements previous research (Moustakas et al., 2020 ; Mrad et al., 2022 ) by adding other key factors to understanding the operational mechanisms of virtual influencer marketing, such as character narratives, forum, promotional characteristics, and community reaction, in addition to authenticity, credibility, and attractiveness.

Third, this study also contributes to the pertinent literature on the authenticity and humanization of virtual influencers. Based on Mori’s Uncanny Valley Theory, previous studies support that accurate human-likeness of virtual influencers led to consumer’s negative effects (Schwind et al., 2018 ). Accordingly, this study classifies current virtual influencers into animalistic, 2D animated, doll-like, and humanoid virtual influencers based on authenticity and humanization. The results reveal that the differences in customer-brand engagement are not affected by the authenticity and humanization of virtual influencers, which is consistent with previous research that not all types of human-likeness virtual influencers cause the uncanny effect (Kätsyri et al., 2015 ; Block and Lovegrove, 2021 ). The present study further indicates that the differences in customer-brand engagement of virtual influencers can be affected by their character narratives in the posts, social media platforms, promotional characteristics, and marketing intentions in the posts.

From a practical perspective, this study also offers some insights for brand and marketing practitioners. For one thing, the high customer-brand engagement of non-branded virtual influencers suggests that there is no need for brands to create their own virtual influencers. Since creating and developing virtual influencers requires significant financial investments by brands, brands may consider partnering with non-branded influencers that already have a broad following and reach to increase customer-brand engagement. For another, the typology of virtual influencers further indicates that brands may consider working with social connectors and brand assistants when selecting virtual influencers in their collaborations, as they have shown higher levels of customer-brand engagement than virtual storytellers and product demonstrators in the study. Finally, brand and marketing practitioners are advised to minimize or avoid presenting their marketing intentions directly or explicitly in virtual influencers’ posts, which, as shown in this study, tends to reduce customer-brand engagement.

Limitations and future research

Naturally, this study has several limitations, which enlighten new directions for future research. For one thing, this study, like previous studies, analyzed virtual influencers on Instagram rather than on different social media platforms. Previous research has shown that customer-brand engagement on social media can be increased by the choice of social media platform (Shen, 2023b ). Therefore, it would be interesting to further investigate the different customer-brand engagement of virtual influencers on Twitter, YouTube, and TikTok, as evidenced by Devereux et al. ( 2020 ), i.e., resource-constrained companies need to make important holistic decisions about which platforms are best suited for marketing their business. For another, this study developed a typology of virtual influencers based on character narratives, forum, promotional characteristics, and community reactions grounded on Kozinets et al. ( 2010 ). In addition to these factors, other factors that may affect customer-brand engagement such as product factors (e.g., product types) and customer factors (e.g., demographic groups) have been proposed in the existing literature (Shao and Ross, 2015 ). Hence, future research could consider continuing to investigate these factors affecting customer-brand engagement of virtual influencers in order to understand them more fully.

Data availability

The data generated and analyzed during the current study are available from https://www.virtualhumans.org/article/instagram-has-verified-35-virtual-influencers .

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Acknowledgements

This work was supported by the Zhejiang Provincial Philosophy and Social Sciences Planning Project (Grant No. 23NDJC151YB); the Scientific Research Fund of Zhejiang Provincial Education Department (Grant No. Y202250373); the Hangzhou Philosophy and Social Sciences Planning Project (Grant No. Z23JC081); Zhejiang Sci-Tech University’s Teaching Reform Research on Exploration and Practice of International Communication Talent Cultivation Based on Global Integrated Classroom, and the Science Foundation of Zhejiang Sci-Tech University (Grant No. 22252284-Y).

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Research   |   UW News blog

October 19, 2022

These factors have the biggest impact on influencer marketing effectiveness

New research from the University of Washington examines how factors related to social media influencers, their posts and their followers impact marketing success. Pixabay

About 70% of people between the ages of 18 and 29 use Instagram, and it’s hard to spend much time scrolling without encountering a sponsored post from an influencer. The same holds true for just about any other social media platform.

New research from the University of Washington examines how factors related to influencers, their posts and their followers impact marketing success. Social media influencers are typically digital creators who have built a large following due to their knowledge on specific topics, such as beauty products, food or pets.

Recently published online and forthcoming in the Journal of Marketing, the study is one of the first to include cost data in its examinations of influencer marketing. Researchers found that if firms spent 1% more on influencer marketing, they would see a nearly 0.5% increase in engagement. They also concluded that reallocating spending based on the study’s insights could result in a 16.6% increase in engagement.

Engagement is the way people react to online content, such as such as liking, commenting or reposting. For this study, researchers prioritized the number of reposts because it represents a deep form of engagement where followers are choosing to share content with their own networks.

Robert Palmatier , co-author and professor of marketing in the UW Foster School of Business, said influencer marketing is currently producing higher return on investment, or ROI, than most other kinds of marketing.

“I predict that in the future, a lot of marketing is going to be crowdsourced,” Palmatier said. “As a marketing manager, you’re going to manage a portfolio of influencers, just like Nike manages a portfolio celebrities.”

For this study, researchers tested data obtained from Weibo, a microblogging website that is one of the largest social media platforms in China. The data consisted of 5,835 posts written by 2,412 influencers related to 1,256 campaigns for 861 brands in October 2018. The brand sponsors spanned 29 categories, including beauty products, e-commerce platforms and food and beverages.

Researchers found that influencer originality, follower size and sponsor salience – the prominence of the brand in a post – enhance the effectiveness of a message, while posts that announce new products diminish it. Followers are less likely to repost product launches due to the heightened risk of vouching for something unknown to their networks.

The influencer’s activity rate, level of post positivity and follower brand-fit, or the degree to which the interests of an influencer’s followers match the sponsor, all produce inverted U-shaped effects. It hurts engagement if influencers post too much, for example, but engagement also suffers if they post too little. This suggests that a balanced approach is most effective.

“If you don’t post, I’m going to forget who you even are,” Palmatier said. “But if you’re doing too much, it kind of cheapens you. It’s what we call an inverted-U shaped effect, which means there is an optimal point of activity where something performs the best.”

When it comes to brand-fit, researchers found that firms should search for influencers with followers that overlap but aren’t an exact match.

“If you’re only talking to people who are most likely to buy your product, those people already know about it,” Palmatier said. “Now if you go to people who are a terrible brand match, they’re never going to buy it because it’s just a poor fit. You want people that have some interest, but probably don’t know about this product.”

Palmatier used Tiffany & Co. as an example of a brand that has successfully utilized influencer marketing. There was a time when the company had trouble acquiring younger customers, he said, because it was mostly popular with longtime consumers.

“If you think about Tiffany’s marketing department, it was probably a group of people that knew their historic targets,” Palmatier said. “What they did was spend a very small part of their budget to bring in some influencers, and those influencers got multiple times higher returns than their own product managers.”

Influencers compete in the free market to increase their followers and engagement, Palmatier said, which is a major factor in their success.

“They had to be clever,” he said. “They had to find a niche. In other words, influencers win their following by understanding their audience very well. When I go to an influencer with my product, they’re going to create posts that resonate with their followers. Tiffany never understood how to position its product for that group, but influencers were able to connect.”

Another advantage of influencer marketing is microtargeting, Palmatier said. Customers can self-segment on social media by following specific topics that interest them. For example, a person might follow hashtags related to Paris before a vacation.

“This is crowdsource positioning,” Palmatier said. “You give influencers a product and they go position it. People also see influencers as being more authentic because mentally, you feel like you’re actually ‘friends’ with the people you follow on social media – even though you’ve never met them – so they appear more authentic when they’re positioning the product.”

Other co-authors were Fine F. Leung and Flora F. Gu of The Hong Kong Polytechnic University; Yiwei Li  of Lingnan University; and Jonathan Z. Zhang of Colorado State University.

The research was supported by Lingnan University’s Direct Grant and Faculty Research Grant.

For more information, contact Palmatier at [email protected] .

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The Role of Social Media Influencers in the Lives of Children and Adolescents

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Using social media influencers to increase knowledge and positive attitudes toward the flu vaccine

Erika bonnevie.

1 Department of Health Communications, The Public Good Projects, New York, NY, United States of America

Sarah D. Rosenberg

Caitlin kummeth.

2 Marketing Department, The Public Good Projects, New York, NY, United States of America

Jaclyn Goldbarg

Ellen wartella.

3 Northwestern University School of Communications, Evanston, IL, United States of America

Associated Data

All relevant data are available from the Open Science Framework database (DOI: 10.17605/OSF.IO/378VD , https://osf.io/378vd/ ).

Seasonal influenza affects millions of people across the United States each year. African Americans and Hispanics have significantly lower vaccination rates, and large-scale campaigns have had difficulty increasing vaccination among these two groups. This study assessed the feasibility of delivering a flu vaccination promotion campaign using influencers, and examined shifts in social norms regarding flu vaccine acceptability after a social media micro influencer campaign. Influencers were asked to choose from vetted messages and create their own original content promoting flu vaccination, which was posted to their social media pages. Content was intentionally unbranded to ensure that it aligned with the look and feel of their pages. Cross-sectional pre- and post-campaign surveys were conducted within regions that received the campaign and control regions to examine potential campaign impact. Digital metrics assessed campaign exposure. Overall, 117 influencers generated 69,495 engagements. Results from the region that received the campaign showed significant increases in positive beliefs about the flu vaccine, and significant decreases in negative community attitudes toward the vaccine. This study suggests that flu campaigns using a ground-up rather than top-down approach can feasibly reach at-risk groups with lower vaccination rates, and shows the potentials of using an influencer-based model to communicate information about flu vaccination on a large scale.

Introduction

Every year, seasonal influenza affects millions of people in the United States. During the 2018–2019 influenza (or flu) season, the flu was involved in up to 20 million hospitalizations and up to 61,000 deaths in the United States [ 1 , 2 ]. One of the most effective ways of preventing the flu is by getting a flu vaccine every year and the U.S. Centers for Disease Control and Prevention recommends all individuals 6 months of age and older receive the flu vaccine each year [ 1 ]. Yet despite the seriousness of the flu, many people do not get vaccinated.

Studies have shown racial and ethnic disparities in flu vaccination rates. Despite the implementation of large-scale flu vaccination campaigns across the U.S., vaccination coverage among African Americans and Hispanics has remained low, with recent flu vaccination coverage for African Americans at 32.3% and for Hispanics at 28.4%, compared to over 40% vaccination coverage for their White and Asian counterparts [ 3 – 5 ]. Negative perceptions toward the flu vaccine may at least partially explain the low flu vaccination coverage, which may lead to social norms that discourage vaccination [ 6 , 7 ]. Studies have shown that African Americans are more likely than other groups to have higher risk perceptions of the flu vaccine and its potential side effects, to mistrust the medical community and government involvement in ensuring safety of the vaccine, and to be uninformed regarding the benefits of flu vaccination [ 8 – 10 ]. Hispanics are less likely than other groups to believe that the flu vaccine is effective, and more likely to fear vaccine side effects [ 11 , 12 ]. Both African Americans and Hispanics are more likely than other groups to believe that the flu vaccine is simply a way for physicians to make a profit [ 13 ]. Conversely, individuals who report that a majority of people around them receive the flu vaccine are in turn more likely to intend on becoming vaccinated themselves [ 14 ]. All of these factors potentially lead to differential vaccination coverage among races and ethnicities within the U.S., and ultimately, a higher morbidity and mortality for African Americans and Hispanics from flu and flu-related illness [ 7 , 15 ].

Given these disparities, there is a need for more information on strategies to reach these populations with positive messages about flu vaccination, using methods that can be applied on a large-scale. Researchers have suggested some technology-based strategies to increase vaccination rates, including digital surveillance technology via electronic medical records, or communications through text messages, email and social media [ 16 – 19 ]. However, many of these methods have not been tested on a large scale for flu vaccination, have not shown effectiveness (particularly among the populations identified above), and may depend on individuals meeting the researchers where they are—for example, on an app [ 19 ]. While researchers have examined the relationship between the use of social media and flu vaccination, there is a lack of information on using social media influencers to deliver health messaging about flu vaccination [ 20 , 21 ]. This study adds new evidence to show the potential uses of a social media influencer model. Social media influencers are individuals on social media who have built a credible reputation and following, oftentimes in a specific niche topic area [ 22 ]. For over a decade, the marketing sector has used social media influencers as a cost efficient and effective way to sell products [ 23 ]. Social media influencers are just starting to be used in public health, with research beginning to show their promise in promoting various health behaviors; social media influencers have shown promise in achieving high levels of digital engagement and positive health outcomes, with researchers calling for more investigation into applications of this model for other behaviors [ 24 – 27 ]. The present study applies these theories to a campaign that promotes positive views of the flu vaccine.

From October 2018 to March 2019, The Public Good Projects (PGP) implemented a digital campaign using social media micro influencers to increase knowledge and positive attitudes toward the flu vaccine among African Americans and Hispanics living in Kaiser Permanente service regions. The campaign employed user-generated content from social media micro influencers whose followers disproportionately represent the campaign’s target audiences in the areas that received the campaign. For the purposes of this campaign, a micro influencer was considered someone with 500 to 10,000 followers on at least one social media account. Micro influencers were utilized because these individuals may be more likely to be perceived as friends or aspirational peers than celebrities or influencers with significantly larger followings. Friends and peers may be well positioned to impact perceptions of vaccines at the interpersonal level, within models of behavior change such as the Social Ecological Model [ 28 ]. Micro influencers often have trusting relationships with their followers, who often reside in a specific geographic region, and these influencers are unlikely to have large, multi-state followings [ 29 ]. The goals of the campaign were to use influencers to deliver messages about the flu vaccine as a way of shifting social norms toward embracing a positive view of the flu vaccine. To date, this is the largest influencer-driven flu vaccination campaign focused on reaching African American and Hispanic communities in the U.S. The objectives of this study were to assess the feasibility and potential acceptability of delivering a flu vaccination promotion campaign through the use of influencers, and to describe any potential differences in flu-related attitudes before and after implementation of the social media influencer campaign.

Influencers were recruited through influencer recruitment software, which contained information on each individual’s geographic reach and proportion of followers who were African American or Hispanic. To ensure that influencers had legitimate followers and were not engaging in “influencer fraud” (for example by purchasing followers), influencer software provided a credibility score which estimated how many followers were actively engaged as well as a follower growth chart to detect spikes in followings that may reflect fraudulent behaviors. These measures allowed PGP to be confident that all influencers who took part in the campaign were not engaging in fraud to grow followers. The platform provides the ability to filter influencers by those who fit demographic and geographic targeting criteria, from their list of over 2 million influencers who are signed up for the platform. An open call was sent to all influencers who met the eligibility criteria, including that their following consisted of a primarily African American or Hispanic audience, located within the area that received the campaign. It is therefore not possible to determine the percentage who viewed the open call to participate in the campaign and refused to take part, or the reasons for non-participation.

Influencers selected for this study created personal messages, images, and/or videos promoting the flu vaccine and posted them on their social media accounts. Influencers were asked to choose from a selection of previously-vetted messages pertaining to flu vaccination and create their own original, user-generated content, in either English or Spanish, promoting flu vaccination using one of those message prompts (for example, “Need a good reason to get a flu shot? How about to protect not just yourself but those you care about most? I’m getting the flu shot this year for my daughter. Check out stopflu.org to find out where to get a flu shot near you. #stopflu”). Due to negative connotations associated with the word “vaccination,” all posts referenced the “flu shot.” Message prompts were changed on a monthly basis and focused on dispelling common myths about the flu vaccination as well as general encouragement to initiate flu vaccination.

Influencers were asked to ensure that their post referenced at least one vetted fact that was provided to them. Facts were pre-selected and related to the following eight categories, which corresponded to common gaps and misconceptions about the flu vaccine and which formed the basis for this study’s evaluation questions: 1. The importance of protecting yourself, your family, and the community; 2. Everyone needs a flu shot, even those who are healthy; 3. Addressing myths (i.e., ‘the flu shot cannot give you the flu’); 4. Highlighting convenience of flu shot locations; 5. The seriousness of the flu; 6. It’s “never too late” to get the flu shot; 7. Safety and efficacy of the flu shot; and 8. Minimal side effects of the flu shot, especially compared to being infected with the flu. While the eight prompt categories were used throughout the season, specific messages changed as the flu season progressed. From September to November, posts focused on preparation; from December to January, posts focused on getting the flu vaccine during flu season; and from February to March, posts focused on the importance of getting the flu vaccine even late in the season. To ensure that prompts were relevant and engaging, influencers were asked to create posts that tied into relatable moments and holidays.

Influencers were not required to respond to comments on their posts, and all responses to engagements with the posts were at the discretion of the individual influencer. Influencers posted one message across each of the platforms on which they were active as an influencer (Facebook, Instagram, and/or Twitter). Each message included a link to the campaign website, stopflu.org . The website complemented influencer posts and inspired action by providing information about where flu vaccination was offered. Upon reaching the website, a user was given two paths: clicking either “I’m a Kaiser Permanente member” or “I’m a member of another system.” Kaiser Permanente members were sent to the health system’s “Health & Wellness” page, where they entered their region to locate a flu clinic. Non-Kaiser Permanente members were sent to a vaccine finder page, where they were able to locate their own local clinic.

Compensation for influencers depended on reach and influence; those with a larger reach and more influence received more compensation. Influencers were compensated up to $360 for their participation, with an average of $84.46 per influencer. The campaign spent approximately $15,000 on payments to influencers. Before participating, influencers were required to pass a 3-month retrospective review of all public social media posts. Vetting criteria included no promotion of alcohol, tobacco, firearm products, or inflammatory or offensive posts of a sexual, political, or bigoted nature.

Content produced by influencers was intentionally unbranded, a term referred to as “native advertising” [ 30 ]. Using unbranded content and relying on the effectiveness of tailored messaging is an established practice in marketing, but is relatively untested within the public health sphere [ 31 , 32 ]. This method of advertising promotes ideas related to a specific behavior change in order to have an effect on behavior that is beneficial to the brand (or in this case, the health behavior). Native advertising matches the message being promoted with the style of content already on the page or individual’s social feed where the promoted message will appear. Native advertising is designed to motivate individuals to adopt a certain behavior, without relying on awareness of campaign brand names. Individuals are more likely to spend time viewing native content compared to content that are clearly advertisements [ 33 , 34 ].

To describe potential differences in flu-related attitudes before and after the campaign, two cross-sectional online evaluation surveys were conducted that included purposively-recruited respondents across campaign and control areas. Campaign areas include eight regions in which the campaign was delivered (corresponding to the regions in which Kaiser Permanente has an active presence): Northern California, Southern California, Colorado, Georgia, Hawaii, Mid-Atlantic States (Maryland, Virginia, and Washington D.C.), Oregon, and Washington. Control areas include the following eight states, chosen to resemble campaign region demographics as closely as possible: Alabama, Arizona, Nevada, New Mexico, New York, Oklahoma, Pennsylvania and South Carolina. The baseline survey was conducted prior to the U.S. flu season, from August 22, 2018 to September 21, 2018. The follow-up survey was conducted after the end of the typical flu season, from March 1, 2019 to April 8, 2019. All respondents included in this study were recruited to participate via research panels from Qualtrics, a research panel company, and were selected to match their representative populations as much as feasibly possible given the recruitment method. Eligibility criteria included being 18 to 64 years of age, Hispanic and/or African American, English or Spanish-speaking, and currently living within one of the identified campaign or control areas. Race and ethnicity were presented as two separate questions, and respondents could choose all races that applied to them. After reading a consent form explaining the nature of participation, each individual was asked to provide electronic informed consent to continue with the survey, which confirmed their enrollment. This study was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans and was reviewed by IntegReview and determined to be exempt from IRB review.

Evaluation survey questions were derived guided by the Theory of Planned Behavior, which states that behavior is determined by attitudes, perceptions of social norms, and beliefs of control or self-efficacy to accomplish the intended behavior change [ 35 ]. The survey assessed respondent demographics and examined social norms regarding the flu vaccine, both before and after the campaign. The survey instrument utilized existing standardized and validated measures of knowledge, attitudes, and reported and intended behavior related to the flu vaccine derived from flu-related surveys conducted across the U.S. (such as the National H1N1 Flu Survey and surveys from the National Foundation for Infectious Diseases), as well as academic research from noted researchers and organizations in the field [ 36 – 39 ]. To determine exposure to the campaign, at follow-up, respondents were asked if they had seen posts that promoted the flu vaccine on their social media pages. To evaluate the feasibility of using an influencer-based campaign to promote flu vaccination, an examination of digital metrics was undertaken to determine the level of engagement generated by influencer posts. Results from the questions in the online survey were compared for various groups (i.e., baseline versus follow-up; exposure to posts versus no exposure to posts) using a 2-sided Pearson Chi-squared test (alpha was set at 0.05), and data were analyzed using IBM SPSS Statistics. An a priori power analysis was conducted to ensure sufficient sample size for statistical comparisons. Google Analytics was used to examine campaign digital metrics. Potential campaign reach was calculated by adding the total number of followers of all influencers.

Feasibility of the campaign

The 117 recruited influencers resided in the following locations: Colorado (n = 10), Georgia (n = 11), Hawaii (n = 10), the Mid-Atlantic States (10 in Maryland, 10 in Washington D.C. and 10 in Virginia), Northern California (n = 13), Oregon (n = 11), Southern California (n = 21), and Washington State (n = 11). Influencers involved in the campaign showed a variety of topic interests typically displayed on their page, with the largest group (31%) being influencers who typically post about parenting, followed by travel influencers (10%). Others included fashion, photography, or health and wellness influencers (all comprising less than 10% of influencer interests). A majority of influencers were female (77.7%), compared to males (19.4%) and couples whose accounts featured multiple people (2.9%). Across all states, 59.4% of influencers reached predominantly African American followers, compared to 36.8% of influencers who reached predominantly Hispanic followers, and 3.8% who reached both.

Throughout the campaign period, the influencers reached a potential of 9.9 million individuals on social media, and generated 69,495 engagements (likes, shares, or comments). Approximately 86% of influencers chose to post an image, 19% chose to post text, and 5% chose to create a video. See S1 File for examples of influencer posts. English posts reached a potential of 8.4 million social media users and generated 49,471 engagements, while Spanish posts reached a potential of 1.5 million individuals and generated 20,424 engagements. The results of the campaign demonstrated that influencer posts generated high levels of engagement, on par with general marketing industry standards. In terms of the engagement rates, Spanish-language posts appeared to be more engaging, with 20,000 engagements across a potential reach of 1.5 million, compared to 50,000 engagements across a potential reach of 8.4 million for English-language posts.

The website attracted 16,064 unique homepage views and page views on the Vaccine Finder page; 76.0% of those who visited the Vaccine Finder page used the tool and entered their zip code to find their nearest vaccination site. A total of 809 unique zip codes were entered into the Vaccine Finder. Of those, 770 were from a state exposed to the campaign, 23 were from states not exposed to the campaign and 16 were invalid. The average time spent on the Vaccine Finder page was 3 minutes and 13 seconds.

Evaluation survey demographics

A total of 4,904 respondents completed the baseline survey ( Table 1 ). Of those, 2,435 resided in campaign areas and 2,469 resided in control areas. The follow-up survey was conducted among 5,447 respondents, with 2,719 residing in campaign areas and 2,728 residing in control areas. More than 50% of respondents in both the baseline and follow-up surveys were in the age range of 18 to 35. Gender distribution was similar between the two survey periods, with slightly more female respondents across both time periods and regions. At both baseline and follow-up, there were more Hispanic respondents in the campaign areas compared to the control areas. Conversely, there were more African American respondents in the control areas compared to campaign areas.

a Data are %(n).

b Race variable are not mutually exclusive. Total N and (%) may not add up to the stratum specific sample sizes.

Previous flu and vaccine history

More than 50% of respondents in the campaign group reported that they receive the flu vaccine every year or most years, while 20% reported they receive the vaccine during some years, and greater than 25% reported that they never get the flu vaccine. These figures were not significantly different between baseline and follow-up for either the campaign or control groups ( Table 2 ). Previous flu vaccination coverage was similar, but differed significantly, between the campaign and control areas ( Table 2 ). At baseline, the campaign and control groups were not significantly divergent in flu vaccine behaviors and intentions at baseline. At follow-up, respondents were asked if they got the flu vaccine during the previous flu season. Respondents in the campaign region reported slightly higher vaccination rates at follow-up, with nearly 45% receiving the vaccine in the campaign group and 42% receiving it in the control group. This difference was not significant.

a Data are % (N).

b Question presented during baseline survey only.

c Question presented during follow-up survey only.

Social norms regarding the flu and flu vaccine

In the campaign area, several measurements of specific knowledge and positive attitudes toward the flu vaccine were statistically significantly higher at follow-up than at baseline ( Table 3 ). In particular, the campaign area had significantly higher percentages at follow-up versus baseline of those who: believe it is never too late to get a flu vaccine (p < .05), disagreed that healthy people do not need to get the flu vaccine (p < .05), believe the government closely monitors the safety of the flu vaccine (p < .05), and agreed that respondents would get the flu vaccine if everyone else was getting it (p < .05). Across these measures, the control area did not show a significantly higher percentages of agreement from baseline to follow-up. The campaign group showed a significantly lower percentage of those who believe that the side effects of the flu vaccine are worse than the flu (p < .05) from baseline (34%) to follow-up (32%), while the control group showed a higher percentage for this measure (p < .05) from baseline (35%) to follow-up (37%).

a Data are % (n).

b Data represents respondents who reported disagreement; all other measures represent respondents who reported agreement.

To understand perceptions of community-wide social norms, questions were also asked to gauge perspectives on family and friends’ attitudes toward the flu vaccine. Within the campaign area, there were several statistically significant decreases at follow-up versus baseline which were not replicated in the control area, including for questions around friends thinking the flu vaccine is not effective and friends thinking the flu vaccine is not safe (both p < .05).

Differences among respondents exposed to posts

Table 4 displays an examination of differences between those who reported that they had seen a message promoting the flu vaccine on social media and those who did not within the campaign region ( Table 4 ). At follow-up, 14.1% of respondents in the campaign region reported seeing positive flu promotion posts from someone they follow on their social media accounts. Those who had seen a flu promotion post on social media reported significant differences across various measures, including higher reported vaccination coverage compared to those who had not seen flu promotions (50.9% vs 43.3%), and significantly more often agreed that the vaccine is effective (58.2% vs 46.8%), that the vaccine is the best way to protect others from the flu, (67.1% vs 55.5%), and that the vaccine is worth the time and effort (67.1% vs 59.1%).

a Data are % (N). Table includes follow-up data for respondents who reported exposure to flu vaccination promotion posts in the campaign region only.

Results from this study of a campaign to affect social norms regarding seasonal flu vaccine among African Americans and Hispanics demonstrated a greater improvement in knowledge and positive perceptions of the flu vaccine among respondents sampled from the campaign area versus those in the control area in the post- campaign follow-up survey. Notably, respondents in the campaign area reported significantly higher agreement with social norms and perceptions of community attitudes conducive to receiving the flu vaccine than those in the control area at follow-up. Additionally, the differences detected in the campaign group were generally significantly higher in the follow-up period versus baseline. Finally, at follow-up, those in the campaign area who reported exposure to campaign posts were significantly more likely to have received the flu vaccine and report positive flu vaccine perceptions than those who did not report exposure to campaign posts.

Regarding the feasibility of using an influencer-based campaign to promote flu vaccination, the examination of digital metrics demonstrated high levels of engagement, signaling that this type of campaign can reach large numbers of people with a relatively limited amount of resources. Although it was not a not a main focal point of this study, another study undertook a qualitative analysis of comments on Stop Flu influencer posts over the course of two years of implementation, finding that on average 94% of comments that were made on influencer posts were of a positive nature [ 40 ]. This finding suggests that individuals will engage in a positive way with vaccine promotion messaging if it is presented from individuals that they already admire or follow. This is particularly important because flu vaccination (and vaccination in general) is a topic that is often subject to heavy debate, and digital campaigns can easily become grounds for the spread of false information and negative sentiment from individuals opposed to vaccinations [ 41 – 43 ]. The health community must react to these negative trends by utilizing new technology and innovative methods to communicate information in places that are less likely to be flooded with anti-vaccination messages, and in ways that will most resonate with at-risk audiences. Targeted messaging is also a critical piece of native advertising and producing effective behavior change campaigns. This study shows that targeted messaging for flu vaccination can be engaging for both English and Spanish–speaking populations. We theorize that the higher rate of engagement within the Spanish-speaking community may result from individuals not being accustomed to seeing health information in Spanish and in a style that resonates with them, so they felt more compelled to engage with the content, compared to those who viewed the English-language content.

In addition to showing the potential to reach African Americans and Hispanics in both English and Spanish, this study revealed other potential audiences that may be ideal to target for future flu vaccination campaigns. Baseline results from the campaign area showed that nearly 25% of respondents had already received the flu vaccine for the upcoming year, while just over 30% intended to do so, and around 15% were unsure. However, the follow-up showed final vaccination coverage around 45% of the sample. This suggests there are at least two groups that may be an ideal audience to target for future campaigns: those who intend on getting the vaccine (but do not), and those who are unsure if they will get the vaccine. Future studies should examine the feasibility of using an influencer-driven model to reach that group who express intention or hesitancy, but may be more receptive to receiving the vaccine. This methodology also has promising implications in communicating information about other topics that are hotly debated, including other non-seasonal vaccinations, particularly in light of recent measles outbreaks [ 44 ].

There are some limitations stemming from employing a cross-sectional panel-based survey. Since the panel company cycles panel participants, it is not possible to conduct a longitudinal study to determine whether a specific group of individuals were affected directly by the campaign. Therefore, all results are meant to demonstrate and test differences among samples at two unique timepoints. This was accomplished by selecting pre- and post- campaign samples of the population that were as similar to each other as possible on major characteristics and also as similar to their represented populations as was possible. While we acknowledge that these samples were not fully representative of the population or perfectly comparable to each other (the baseline and follow-up samples differed by age and race, but not on age), through triangulation of data, we believe our campaign did have the intended effect on the larger population, as analyses revealed that those who reported exposure to a campaign were more likely to report positive flu vaccination perceptions and, indeed, to receive a flu vaccine than those who were not exposed to a campaign. However, we were not able to control for all confounding factors, such as the level of participant vaccine education or the presence of vaccine drives in campaign or control communities. Survey respondents may show desirability bias or may not represent the general audience. This limitation may have been mitigated by the fact that panel participants are routinely cycled in and out of panels to avoid creating a pool of professional survey takers. The fact that the survey was completed online may have made respondents more likely to provide their honest opinions.

Other limitations of this study include that the severity of the flu season can affect changes in the constructs measured in the survey. However, data on the percentage of visits to outpatient clinics for Influenza-Like Illness (ILI) and the percentage of deaths resulting in pneumonia or influenza (measurements used to determine severity) presented similar results for both the campaign and control region, suggesting that both regions experienced similarly severe flu seasons [ 45 , 46 ]. Although influencers were chosen based on their number of followers within campaign areas, it is possible that social media users outside the campaign areas also viewed their content. This result would be considered non-problematic in non-control areas, as these messages could be positively influential outside the campaign area. If these messages positively influenced persons in the control area, however, this potentially decreased our ability to detect differences between the campaign and control groups. Nevertheless, we found significant differences between these groups. Additionally, the metric of “potential reach” may overestimate the number of followers who actually viewed the content; however, this metric is an industry standard, given that is it often not possible to view actual reach when using influencers to deliver messaging (as was the case with this study). Finally, it is possible that those exposed to the campaign already had more positive attitudes toward the flu vaccine compared to the general population.

Conclusions

This study shows that the approach of using influencers to deliver positive flu vaccine-related information is a promising strategy for communicating health information, changing flu vaccination perceptions, and possibly flu vaccine seeking behavior. Influencers can be an ideal tool for health communication if they already identify with a target audience, and their content uses the same language and style of speech that the audience uses. In this way, health campaigns can have a look, feel, and sound that will capture an audience’s attention. While the strategy of using unbranded native advertising techniques does not allow for an easy comparison of behavior change associated with campaign exposure, results showed encouraging results among those who reported awareness of a flu vaccine campaign on social media. We demonstrated that those who were exposed to the campaign were more likely to receive the flu vaccination and report positive flu vaccination perceptions. We feel that this presents an important step toward using innovative methodologies to communicate health information. This approach may be particularly important within the context of the COVID-19 pandemic. Health experts have expressed concern that the 2020–2021 flu season could present additional challenges to individual health, and could place strains on healthcare systems which may need to address both a COVID-19 pandemic and a flu season at the same time [ 47 ]. Given that African Americans and Hispanics are disproportionately affected by COVID-19 and are less likely to get the flu vaccine compared to other demographic groups, it is critical to employ new approaches that can deliver positive messages about vaccination to these groups [ 48 ].

Future studies should also examine how to address the challenge of evaluation using native advertising strategies which place the message at the center of the campaign, instead of a brand name. The marketing industry has acknowledged the fact that individuals are keenly aware when they are being advertised to; strategies to change behaviors must take into account new approaches to creating health campaigns [ 49 – 51 ]. Most studies using influencers to improve health behaviors have relied on campaign awareness or digital metrics to evaluate success. However, these metrics are often simply a reflection of digital ad spending, rather than an evaluation of behavior change [ 52 , 53 ]. While the evaluation methodology employed in this study contained its limitations, it presents an alternative strategy of measuring success that merits further examination.

To effectively reach groups that show lower flu vaccination rates, we believe that national or large-scale flu campaigns must take a ground-up rather than top-down approach. By strategically leveraging community- and state-based influencers, and more tactically employing paid and earned media opportunities, flu campaigns can better reach priority audiences, increase positive perceptions about flu vaccination, and ultimately increase vaccination coverage.

Supporting information

Funding statement.

This work was supported by Kaiser Permanente. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability

234 Social Media Research Topics & Ideas

• Icon Calendar 18 May 2024
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Social media research encompasses a broad range of different topics that delve into the ever-evolving digital landscape. People investigate the impact of social platforms on society, exploring subjects, such as online identity formation, self-presentation, the psychology of virtual interactions, and others. Additionally, studies examine the influence of social media on politics, activism, and public opinion, uncovering patterns of information dissemination and polarization. Privacy concerns, cyberbullying, and online safety are also explored in-depth, seeking strategies to mitigate the associated risks. In this article, people can find many social media research topics, ideas, and examples.

Hot Social Media Research Topics

• Impacts of Social Media and Internet Algorithms on User Experience
• The Rise of TikTok: A Socio-Cultural Analysis
• Dealing With Cyberbullying: Strategies and Solutions
• Understanding the Phenomenon of Social Media ‘Cancel Culture’
• NFTs and Social Media: The Future of Digital Art?
• Ethical Concerns in the Era of Influencer Marketing
• Social Media’s Role in Accelerating E-Commerce Growth
• Impacts of Internet and Social Media on Journalism and News Reporting
• Understanding the Psychology of Viral Challenges on Social Platforms
• Cryptocurrency and Social Media: The Intersection
• Mitigating Misinformation and ‘Fake News’ on Social Media
• Augmented Reality (AR) in Social Media: A Game Changer?
• Evaluating the Impact of Social Media on Political Campaigns
• Social Media’s Influence on Fashion and Beauty Trends
• Privacy, Safety, and Security Concerns in the Age of Social Networking
• Roles of Free Access and Social Media in Promoting Sustainable Practices
• Implications of Social Media Addiction on Mental Health
• Examining Social Media’s Role in Crisis Communication
• The Power of User-Generated Content in Branding
• Influence of Social Media on Food Culture and Dining Trends

Easy Social Media Research Topics

• Impacts of Online Videos and Social Media on Mental Health
• Influencer Marketing: Efficacy and Ethical Concerns
• Evolution of Privacy Policies Across Social Platforms
• Understanding Virality: What Makes Content Shareable?
• Cyberbullying: Prevalence and Prevention Strategies
• Social Media and Political Polarization: An In-Depth Study
• Role of Social Media in Modern Business Strategies
• Effect of Social Media on Interpersonal Relationships
• Social Platforms as Tools for Social Change
• Navigating Online Hate Speech: A Legal Perspective
• Emerging Trends in Social Media Advertising
• Online Identity Construction and Self-Presentation
• The Psychology of Social Media Addiction
• Social Media’s Role in Crisis Management and Communication
• Sentiment Analysis in Social Media and Its Implications
• Social Media Algorithms: Bias and Implications
• The Phenomenon of Cancel Culture on Social Platforms
• Cybersecurity Threats in the Era of Social Media
• Analyzing Adverse Impacts of Social Media on Consumer Behavior

Interesting Social Media Research Topics

• Evaluating the Effects of Social Media on Language and Communication
• Roles of Social Media in Fostering Political Engagement
• Misinformation and Propaganda Spread Through Social Platforms
• Analyzing the Shift From Traditional Media to Social Media
• Dark Patterns in Social Media: Hidden Manipulative Tactics
• Social Media and Digital Activism: Revolutionizing Advocacy
• Augmented Reality (AR) and Its Impact on Social Networking
• Exploring Cybersecurity Issues in Social Media Platforms
• Roles and Effects of Social Media and News in Mental Health Promotion
• Strategies for Effective Social Media Crisis Management
• The Power of Live Streaming for Brands and Influencers
• Using Social Media to Enhance Classroom Learning
• Analyzing the Influence of Memes on Internet Culture
• Impacts of Social Media Algorithms on User Behavior
• Assessing the Correlation Between Social Media and Loneliness
• Geotagging and Its Implications for Personal Privacy
• Social Media and E-commerce: A Cross-Industry Study
• The Ethics of Digital Advertising on Social Platforms
• Understanding the Psychology of Social Media Trolls
• The Cultural Shift Caused by Social Media Localization

Social Media Research Paper Topics for High School

• The Phenomenon of Cyberbullying: Prevention and Strategies
• How Does Social Media Influence Teen Body Image?
• Evaluating the Educational Potential of Social Media Platforms
• Impacts of Social Media on Adolescents’ Self-Esteem
• Roles of Free Connection and Social Media in Modern Political Activism
• Exploring the Concept of ‘Digital Citizenship’ Among Teenagers
• The Ethics of Social Media Privacy: User Rights and Responsibilities
• Social Media Addiction: Understanding Its Causes and Effects
• Influence of Social Media on Modern Communication Styles
• Analyzing Positive Roles of Social Media in Promoting Reading Culture
• Social Media and Mental Health: Correlation or Causation?
• The Role of Social Media in Global Environmental Awareness
• Examining Social Media’s Impact on Real-Life Social Skills
• Social Media Platforms: Tools for Personal Branding or Narcissism?
• Influence of Social Media Trends on Youth Fashion Choices
• Impacts of Social Media on Teenagers’ Sleep Patterns
• Online Safety: The Role of Parents and Schools in Social Media Usage
• How Does Social Media Influence Teenagers’ Views on Relationships?
• Social Media and Empathy: Does Online Interaction Decrease Compassion?

Social Media Research Paper Topics for College Students

• Evaluating the Impact of Social Media on Body Image and Self-Esteem
• The Influence of Social Media on Voting Patterns Among Young Adults
• Social Media as a Valid Tool for Social Change: A Case Study Approach
• Unveiling the Psychology of Social Media Addiction
• Social Media’s Role in Modern Journalism: Opportunities and Challenges
• Privacy Implications of Data Collection on Social Media Platforms
• Cyberbullying in the Age of Social Media: Scope and Solutions
• The Ethical Aspects of Social Media Influencer Marketing
• Roles and Effects of Social Media in Crisis Communication and Management
• Social Media and Its Effects on Interpersonal Communication Skills
• Analyzing Social Media Strategies of Successful Businesses
• Impacts of Internet Use and Social Media on Mental Health Among College Students
• The Roles That Social Media Has in Modern Political Campaigns
• Understanding the Social Media Algorithm: Bias and Implications
• Social Media and Consumer Behavior: The Power of Influencer Marketing
• Fake News, Authors, and Disinformation Spread Through Social Media Platforms
• Exploring Direct Links Between Social Media Use and Academic Performance
• Social Media’s Role in Promoting Sustainable Lifestyle Choices
• Regulation of Hate Speech and Offensive Content on Social Media
• The Power and Peril of Virality in the Age of Social Media

Social Media Research Paper Topics for University

• The Effect That Social Media Has on Global Politics
• The Ethics of Data Mining in Social Media
• Roles of Social Media in Business Marketing Strategies
• Social Media, Internet Use, and Their Impacts on Mental Health: A Systematic Review
• Algorithmic Bias in Social Media Platforms: Causes and Consequences
• The Influence of Colors and Social Media on Consumer Behavior
• Exploring Possible Relationships Between Social Media Use and Academic Performance
• Privacy, Morality, and Security Concerns in the Age of Social Media
• Social Media as a Platform for Digital Activism
• Impacts of Social Media on Interpersonal Communication and Relationships
• Cyberbullying on Social Media: Scope, Impact, and Preventive Measures
• The Role of Social Media in Spreading Health-Related Misinformation
• Analyzing the Effect of Social Media on Journalism Practices
• Understanding the Influence of Social Media on Body Image Perceptions
• Social Media’s Role in Crisis Management: Case Studies
• The Power and Effectiveness of Influencer Marketing on Social Media
• Fake News and Disinformation in the Social Media Age
• Regulatory Approaches to Hate Speech on Social Media Platforms
• The Economic Implications of Social Media: From Startups to Giants

Social Media Research Paper Topics for Masters

• Advanced Algorithms and Their Role in Shaping Social Media Interactions
• Evaluating the Impact of Social Media on Democratic Processes Globally
• The Intersection of Privacy, Data Mining, and Ethics in Social Media
• Quantitative Analysis of Social Media’s Impact on Consumer Buying Behavior
• Cybersecurity Threats in Social Media: Mitigation and Prevention Strategies
• Analyzing the Psychological Implications of Social Media Addiction
• Using Social Media Data to Predict Market Trends: An Econometric Approach
• Role of Social Media in Crisis Management: A Comparative Study
• The Sociolinguistic Impact of Social Media on Communication
• Machine Learning and AI in Social Media: An Examination of Emerging Trends
• Social Media as a Valid Tool for Public Health: Opportunities and Challenges
• Social Media’s Influence on Modern Journalism: A Critical Analysis
• Mapping Social Networks: A Graph Theory Approach
• Evaluating the Efficacy of Social Media Campaigns in Social Change Movements
• Analyzing the Role of Social Media in Corporate Reputation Management
• Data Privacy Laws and Social Media: A Comparative Study
• The Use of Small and Big Data Analytics in Social Media Marketing
• Social Media and Its Role in Strengthening Democracy: A Deep Dive
• The Impact of Social Media on Cultural Assimilation and Identity
• Ethics of Artificial Intelligence in Social Media Content Moderation

Social Media Research Paper Topics for Ph.D.

• Analyzing the Impact of Social Media Algorithms on User Behavior and Perceptions
• Deciphering the Influence of Social Media on Political Campaign Strategies
• Examining the Role of Social Media in Corporate Social Responsibility Initiatives
• Social Media and Mental Health: A Comprehensive Analysis of Recent Studies
• Effects of Social Media and Internet Use on Consumer Buying Behavior: An Econometric Approach
• Social Media and Digital Diplomacy: A Critical Analysis
• Ethical Implications of Data Mining Techniques in Social Media Platforms
• Unpacking the Psychological Mechanisms of Social Media Addiction
• Role of Social Media in Contemporary Journalism: Opportunities and Challenges
• Social Media and Privacy: A Comparative Study of Data Protection Laws
• Machine Learning and AI in Social Media: Identifying Future Trends
• Social Media’s Possible Influence on People, Body Image, and Self-Esteem: A Meta-Analysis
• Analyzing the Role of Social Media in Crisis Management and Communication
• Impacts of Social Media on Different Language and Communication Styles
• Cybersecurity in Social Media: An Analysis of Current Threats and Mitigation Strategies
• Social Media as a Good Tool for Health Promotion and Disease Prevention
• Effects of Social Media on Children and Their Parents: Social Skills and Interpersonal Relationships
• Roles of Social Media in Promoting Gender Equality and Women’s Rights
• Social Media and its Influence on Cultural Assimilation and Identity Formation

Social Media Research Topics for Argumentative Papers

• Impacts of Social Media on Social and Political Discourses: Enhancing or Hindering Democratic Engagement?
• Social Media and Mental Health: Exploring the Association Between Excessive Usage and Psychological Well-Being
• Fostering Online Activism and Social Movements: The Role of Social Media
• Balancing Personal Information Sharing and Data Protection: Social Media and Privacy
• Exploring the Effects of Social Media on Body Image and Self-Esteem
• Social Media and Political Polarization: Reinforcing Echo Chambers or Encouraging Diverse Perspectives?
• Youth Culture and Identity Formation: The Influence of Social Media
• Fake News and Misinformation: Combating Inaccurate Information in the Era of Social Media
• Social Media and Cyberbullying: Examining the Impact on Mental Health and Well-Being
• The Ethics of Social Media Research: Privacy, Informed Consent, and Ethical Considerations
• Relationships in the Digital Age: Exploring the Influence of Social Media Use
• The Influence of Internet, Technology, and Social Media on Consumer Behavior and Buying Decisions
• Analyzing the Role of Online Platforms in Elections: Social Media and Political Campaigns
• Social Media in Education: Exploring the Benefits and Challenges of Integration in the Classroom
• Impacts of Social Media and Interface on News Consumption and Journalism Practices
• Body Politics in the Digital Space: Examining Representations of Gender, Race, and Body Image on Social Media
• Addressing Ethical and Security Concerns in the Digital Age: Social Media and Cybersecurity
• Shaping Consumer Behavior and Brand Perception: The Role of Social Media Influencers
• Civic Engagement in the Digital Era: Assessing the Role of Social Media Platforms
• The Influence of Social Media Algorithms on Information Consumption and Personalization

Social Media Research Topics for Persuasive Papers

• The Power of Social Media in Driving Social and Political Change
• Promoting Digital Literacy: Empowering Users to Navigate the Complexities of Social Media
• Social Media as a Catalyst for Social Justice Movements: Amplifying Marginalized Voices
• Countering Fake News and Misinformation on Social Media: Strategies for Critical Thinking
• Harnessing the Influence of Social Media for Environmental Activism and Sustainability
• The Dark Side of Social Media: Addressing Online Harassment and Cyberbullying
• Influencer Marketing: Ethical Considerations and Consumer Protection in the Digital Age
• Leveraging Social Media for Public Health Campaigns: Increasing Awareness and Behavioral Change
• Social Media and Mental Health: Promoting Well-Being in a Hyperconnected World
• Navigating the Privacy Paradox: Balancing Convenience and Personal Data Protection on Social Media
• Roles of Social Media and Internet in Fostering Civic Engagement and Democratic Participation
• Promoting Positive Body Image on Social Media: Redefining Beauty Standards and Empowering Individuals
• Enhancing Online Safety: Developing Policies and Regulations for Social Media Platforms
• Social Media and the Spread of Disinformation: Combating the Infodemic
• Roles of Social Media and Technology in Building and Sustaining Relationships: Connecting in a Digital Era
• Influencer Culture and Materialism: Examining the Impact on Consumer Behavior
• Social Media and Education: Maximizing Learning Opportunities and Bridging the Digital Divide
• The Power of Viral Hashtags: Exploring Social Movements and Online Activism
• Social Media and Political Polarization: Bridging Divides and Encouraging Constructive Dialogue

Social Media Topics for Pros and Cons Research Papers

• Examining the Social Effects of Digital Connectivity: Pros and Cons of Using Social Media
• Balancing Privacy Concerns in the Digital Age: Evaluating the Cons and Risks of Social Media Use
• Information Sharing in the Digital Era: Uncovering the Advantages of Social Media Platforms
• Building Online Communities: Analyzing the Strengths and Weaknesses of Social Media Interaction
• Navigating Political Discourse in the Digital Age: The Disadvantages of Social Media Engagement
• Mental Health in the Digital Sphere: Understanding the Benefits and Drawbacks of Social Media
• Combating Cyberbullying: Addressing the Negative Side of Online Social Interactions
• Personal Branding in the Digital Landscape: Empowerment vs. Self-Objectification on Social Media
• Establishing Meaningful Connections: Exploring the Pros and Cons of Social Media Relationships
• Leveraging the Educational Potential of Digital Platforms: Examining the Benefits of Social Media in Learning
• Body Image and Self-Esteem in the Age of Social Media: Weighing the Positives and Negatives
• From Digital Activism to Political Change: Assessing the Opportunities and Limitations of Social Media
• Unraveling the Influence: Social Media and Consumer Behavior in the Digital Marketplace
• Misinformation in the Digital Landscape: The Pros and Cons of Social Media in the Spread of Disinformation
• Crisis Communication in the Digital Age: Navigating the Benefits and Challenges of Social Media
• Tackling Fake News: Navigating Misinformation in the Era of Social Media
• Maximizing Business Opportunities: Evaluating the Advantages and Disadvantages of Social Media Marketing
• The Psychology of Social Media: Analyzing the Upsides and Downsides of Digital Engagement
• Exploring the Impact of Social Media on Socialization: Benefits, Drawbacks, and Implications
• Online Activism: The Power and Limitations of Social Media Movements

Social Media Topics for Cause and Effect Research Papers

• Enhancing Political Activism: Exploring the Relationship Between Social Media and Civic Engagement
• The Psychological Effects of Digital Connectivity: Investigating the Relationship Between Mental Health of People and Social Media Use
• Political Polarization in the Online Sphere: Understanding the Impact of Digital Networks
• Disrupted Sleep Patterns in the Digital Era: Exploring the Role of Online Platforms
• Digital Distractions and Academic Performance: Analyzing the Effects of Online Engagement
• Navigating Online Relationships: Understanding the Impacts of Digital Interactions
• The Digital Marketplace: Exploring Consumer Behavior in the Age of Online Platforms
• The Loneliness Epidemic: Investigating the Relationship Between Social Media Use and Social Isolation
• Redefining Political Participation: The Influence of Digital Networks on Democracy
• Unmasking Digital Identities: The Psychological Effects of Social Media Use
• News Consumption in the Digital Era: Exploring the Impacts of Online Platforms
• Cyberbullying in the Virtual World: Analyzing the Effects of Online Interactions
• The Digital Campaign Trail: Investigating the Influence of Online Platforms on Voter Behavior
• Fear of Missing Out (FOMO) in the Digital Age: Exploring the Psychological Consequences
• Body Dissatisfaction in the Digital Sphere: Understanding the Impacts of Online Presence
• Information Overload: Coping With the Digital Deluge in the Information Age
• Privacy Concerns in the Online Landscape: Analyzing the Implications of Digital Footprints
• Unveiling the Dark Side: Exploring the Relationship Between Online Activities and Substance Abuse
• Bridging the Political Divide: The Impact of Digital Networks on Sociopolitical Polarization

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Please note you do not have access to teaching notes, attractiveness, trustworthiness and expertise – social influencers’ winning formula.

Journal of Product & Brand Management

ISSN : 1061-0421

Article publication date: 20 July 2020

Issue publication date: 21 May 2021

The importance of influencer marketing is constantly growing. However, little empirical research has examined influencers’ success requirements. This study aims to fill this gap by exploring whether the requirements of influencers’ attractiveness, expertise and trustworthiness are relevant for online influencer campaigns. An entry-level luxury fashion brand is the focus of the experiment.

Design/methodology/approach

A total of 288 participants completed an online survey evaluating the profiles of influencers who varied in terms of the three abovementioned requirements. The impacts of these requirements on brand image, brand satisfaction and brand trust as well as purchase intention and price premium were tested via structural equation modeling.

The results show that the most important requirement is trustworthiness, followed by attractiveness; surprisingly, the relevance of expertise is virtually nil.

Research limitations/implications

To date, practitioners are still struggling with the success requirements of influencer marketing. They have focused on traditional advertising models and numeric requirements such as the amount of followers. However, regarding merely these requirements can result in wrong decisions. Considering the two requirements, attractiveness and trustworthiness, in a stronger way can provide a remedy to this struggle. In future research, the relevance of the requirements in different involvement conditions and for non-attractiveness-related products might be investigated.

Originality/value

To the best of the authors’ knowledge, this study is one of the first to explore the success requirements that are directly related to influencers (e.g. attractiveness) rather than numeric requirements of their profiles (e.g. page rank) and the impacts of those requirements on brand image, brand satisfaction and brand trust as well as purchase intention and price premium. It adapts the Source-Credibility Model for influencers and shows that its requirements interact in a unique way that is counterintuitive and different from other endorser types such as celebrities or salespersons.

• Luxury marketing
• Influencer marketing
• Social media marketing
• Attractiveness
• Trustworthiness

Wiedmann, K.-P. and von Mettenheim, W. (2021), "Attractiveness, trustworthiness and expertise – social influencers’ winning formula?", Journal of Product & Brand Management , Vol. 30 No. 5, pp. 707-725. https://doi.org/10.1108/JPBM-06-2019-2442

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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Influencer research: What do consumers want?

September 1, 2023

Below are the results from our latest research peak , where we wanted to find out what “influencer” means to consumers — are influencers trusted? What current trends are we seeing in the influencer sphere? We surveyed 9,000 global shoppers to find out, and more.

Wondering about the best moisturizer for dry skin? Or, which eyeshadow or nail polish colors are in next season? You might ask a friend or family member. The next best thing is usually to take the advice of a social media influencer. 

All consumers (that’s right: 100% ) have purchased a product based on a recommendation from another shopper that they’ve found online, according to a recent survey of nearly 9,000 global shoppers.

Our research continues to emphasize the power of everyday shoppers to influence each other. 53% of consumers say user-generated content (UGC), like photos from real shoppers or customer reviews, makes them feel more confident buying things online. The reason: these influencers present more authentic content than professional photos, expertly written copy, and traditional marketing messages. 

But before we delve further into the influencer research, there’s a question that needs answering.

What is an influencer?

In influencer, often known as a creator, is a person (or animal, to be honest) who has the ability to influence potential buyers of a product or service by promoting or recommending the items on their social media platform, predominantly TikTok or Instagram.

There’s five types of influencer, each with varying follower counts:

• Subject matter experts : Beauty gurus, fashionistas, chefs, DIY’ers, and stay-at-home moms. These influencers are experts in a specific subject, which they tend to exclusively, or primarily, post about. They often recommend, sell, or post sponsored content for products related to their subject matter 
• Celebrities : These accounts give you a behind the scenes look at those with extravagant lives who have become famous for something other than social media. They can be actors, reality TV stars, musicians, athletes, etc. They often promote/recommend products that fit in with their lifestyle/aesthetic, or that they’re selling themselves
• Social media stars : These are influencers who became famous solely because of their internet presence. They don’t necessarily have a subject matter they’re experts on. They maybe have a very pleasing aesthetic, or an ability to do internet trends well, like TikTok dances. Sometimes they became famous due to a viral moment, and the fame just never faded. Other times they’re just everyday people who post outfit of the day photos and naturally amassed a large following. They’re often paid to promote products or will promote something they are selling themselves
• Everyday social media users : Your friends, family members, peers, or people you’ve never met but are connected to. They simply share day-to-day content (ratings and reviews, photos and videos) that they’re genuinely interested in. They don’t have an agenda to promote or highlight certain products
• Creators : Anyone who creates entertaining or educational material to be expressed through any medium or channel

Influencer research report key takeaways 

As you develop and refine your influencer strategies , here’s the top trends and takeaways to know, as revealed by our research. 

1. Everyday social media users resonate most 

Influencers with massive social media followings and big-name celebrities don’t resonate with shoppers like they used to. These days, consumers prefer the opinions and advice of real people. 

Our research found that 82% of consumers are purchasing more or the same number of products from the recommendation of everyday social media users. Shoppers are more influenced by everyday social media users, who might not have a large number of followers, than brands, celebrities, social media influencers, and subject matter experts. 

Everyday social media users are viewed as more trustworthy. 33% of consumers say their trust in them has increased over the past five years, while 45% say it’s stayed the same. 

As you’re choosing influencers to work with, know that 64% of people want brands to partner with everyday social media users more than anyone else. 

2. Trust in subject matter experts is increasing

Subject matter experts, like a doctor, esthetician, or someone else with official credentials, are also perceived as trustworthy and authentic. 

26% of consumers are most influenced by the opinions of subject matter experts when purchasing products. 33% have actually purchased a product based on an expert’s recommendation. 

Over the past five years, 86% of consumers say their trust in subject matter experts has increased or stayed the same. So, having these experts try out or otherwise showcase your products on social media builds loyalty and drives purchases. 

3. Consumers are more conscious in the ‘de-influencing’ age 

You’ve probably seen reports of Gen Z consumers embracing “ de-influencing ,” which is where social media influencers tell their followers what not to buy. 

While this term has trended on social media channels, our survey found that it hasn’t actually had much of an impact on consumer perception or purchasing habits. 73% of survey respondents haven’t heard of the “de-influencing” trend, and 38% weren’t likely to participate in a #deinfluencing activity.

Among those who have heard of it, 50% say it’s made them more conscious of how they interact with social media influencers online who are promoting a product. 38% say it’s inspired them to conduct more product research before buying. 

4. Consumers rely on influencers for authenticity 

Even though “de-influencing” is playing a big role, consumers want truthful, authentic viewpoints on products. That’s why they see just as much value in negative reviews as positive ones. 

Social media is where people go for product inspiration and information, and to purchase items. Facebook (25%), Instagram (23%), and TikTok (22%) are most used for new product discovery, our survey revealed. 

Shoppers use Facebook (28%), Instagram (23%), and TikTok (18%) the most for purchasing. 

Featuring everyday social media users, subject matter experts, and other influencers on these platforms builds trust. “They give me their honest opinion” is the main quality that people are looking for in influencers, according to 42% of survey respondents. 

They also appreciate influencers because “they share new products I’ve never heard of,” “they have a specialist area they share content, products about,” and they share “fun, engaging content.”

5. Consumers are content creators 

Browsing and posting on social media is a favorite pastime for most people. 82% consider themselves everyday social users, and about 50% spend up to 10 hours a week creating social content . TikTok and Instagram are their favorite social platforms. 

Nearly 40% of people in our survey want to be full-fledged content creators in the future. 41% haven’t done it yet because they don’t know where to start. 

People enjoy posting about products and brands. 79% at least sometimes tag brands in their posts, mainly because they’re fans and want to share their content with their favorite brands. 

Among consumers who are content creators, 49% have partnered with brands on sponsored content, but they’re focused on ensuring that their content is authentic. 62% have turned down brand partnerships, because the partnership didn’t align with their values or the brand wasn’t a good fit.

To maintain authenticity and creative control, they only work with brands and products that they use (26%), give their complete and honest feedback about a product (28%), say when it’s a paid partnership (24%), and only work with brands and products that align with their values (21%). 

6. User-generated content is the biggest influencer on purchasing decisions

One of the big takeaways from our influencer research was that UGC, including ratings, photos, and videos from real shoppers, influences purchasing decisions. Even after seeing something on social media, most consumers visit a brand or retailer’s website to read reviews . 

When they seek out reviews, the factors that ultimately help them decide whether or not to purchase include: 

• “The review includes relevant attributes based on the product (i.e., scent description for a perfume)” (36%)
• “There is a photo with a review” (19%)
• “There is a video with a review” (18%)
• “It includes information about the reviewer, such as skin type, age, size,” (15%) 
• “Length of review” (12%)

When shoppers encounter visual UGC on a product page or social media channel, 47% want the photo to show “the product being used in the way it’s intended,” such as clothing on someone who wears their size or a piece of furniture in a small apartment like theirs. 

Use research to guide your influencer strategy 

If you’re a brand or retailer interested in incorporating influencers into your marketing strategy, you probably won’t have to pay the big bucks. Sending free products to everyday consumers through product sampling and asking them to post their thoughts about your product on social media in return, can pay off dividends.

Or you can follow global brands like kraft Heinz and Rimmel and tap into the Influenster community of over 7.5 million engaged, everyday consumers. All of whom are ready to create content for you. Learn more about it here.

Lauren Venticinque

Marketing Communications Manager

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JSmol Viewer

Brands’ green activism: an empirical comparison between posts of digital influencers and brands.

1. Introduction

2. conceptual background, 2.1. overview of the proposed conceptual background, 2.2. the influence of brand [green] activism on brand equity, 2.3. the role of digital influencers in shaping brand equity, 2.4. gen z’s influence on digital influencers and activism, 2.5. challenges and issues in digital influencer activism, 3. material and methods, 3.1. framework, 3.2. research design, 3.3. questionnaire design, 3.4. data collection.

• Benefits the society/world [Var 1]
• Seems to benefit people [Var 2]
• Made you have a positive opinion about the brand [Var 3]
• Changed your view about the brand [Var 4]
• Changed your view on the cause [Var 5]
• Is a genuine contribution to the cause [Var 6]
• The intention is more to make a profit than to collaborate with society [Var 7]
• May positively affect your intention to buy that brand [Var 8]

3.5. Data and Sample

5. conclusions and implications, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, appendix a. examples of brands’ posts, appendix b. examples of influencers’ posts.

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Share and Cite

Silveira, P.D.; Sandes, F.S.; Xara-Brasil, D.; Menezes, K. Brands’ Green Activism: An Empirical Comparison between Posts of Digital Influencers and Brands. Sustainability 2024 , 16 , 6863. https://doi.org/10.3390/su16166863

Silveira PD, Sandes FS, Xara-Brasil D, Menezes K. Brands’ Green Activism: An Empirical Comparison between Posts of Digital Influencers and Brands. Sustainability . 2024; 16(16):6863. https://doi.org/10.3390/su16166863

Silveira, Paulo Duarte, Fábio Shimabukuro Sandes, Duarte Xara-Brasil, and Karla Menezes. 2024. "Brands’ Green Activism: An Empirical Comparison between Posts of Digital Influencers and Brands" Sustainability 16, no. 16: 6863. https://doi.org/10.3390/su16166863

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Doctoral Dissertations and Projects

The influence of internet media on young adult development.

Michael A. Ouellette , Liberty University Follow

School of Behavioral Sciences

Doctor of Philosophy in Psychology (PhD)

Cari Oliver

Media, Influence, Development, Free will, Young adults

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Ouellette, Michael A., "The Influence of Internet Media on Young Adult Development" (2024). Doctoral Dissertations and Projects . 5870. https://digitalcommons.liberty.edu/doctoral/5870

The study examines from a Christian worldview how free will, regarded as God's greatest gift, is now being shaped by human influence. New treatment methods become essential to adapt to the media-changing world and help with developmental delays. The purpose of this qualitative grounded theory lite study was to explore Internet media’s influence on young adults in Quebec, Canada. Data on Internet media demographics, social behavior, identity, influence, emotional self-regulation, and moral decision-making were collected by conducting twelve semi-structured, audio-recorded interviews with young adults in Quebec. The responses were coded into six primary themes, with an intercoder conducting a cross-verification to enhance the validity of the coding process. The interviews revolved around the three research questions on how the experiences of young adults with heavy internet media use relate to social behavior, identity, and self-regulation developmental delays. Participants were 18 to 32 years old, with no struggles with identity, previous diagnosis, or trauma. The results showed that all twelve participants were heavy media users and eleven of them used it for entertainment. Some results supported it while others refuted previous research on media influence on development. The implications of the data closed the gap regarding the extent Internet media influences social (identity and social behavior) and socio-emotional (self-regulation of emotions) development, by adding qualitative data to quantitative numbers. Understanding these relationships and their signs will better prepare those in a helping role (counselors, therapists, and all caregivers) to monitor and intervene.

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Do users find information from social media tech influencers helpful? Nearly three in five do

We may follow social media influencers for multiple reasons - perhaps for the best fashion deal, restaurant recommendations, or even for tutorials on how to perfect that bench press or bicep curl. But when it comes to technology, do users find information shared by social media influencers useful? 

A recent YouGov Surveys: Serviced poll asked consumers across 17 international markets about topics they find influencers to be useful sources of information for.

Survey data reveals that nearly three in ten consumers (58%) across markets find social media influencers as a useful source of tech information - placing the category among the top three in our list of topics. 

How do different countries perceive the usefulness of social media influencers for tech information?

Data from individual markets reveals that Indonesians (94%) top the list of markets where consumers are most likely to find social media influencers useful for tech-related information. Users in India (86%) and the UAE (84%) follow those in Indonesia, with Mexicans (76%) and Hong Kongers (75%) completing the top five ranks. 

Nearly three fourths (72%) of users in Singapore (home to popular tech influencers like Julian Tay and Jack) also find social media influencers to be useful sources of information for tech - so do more than half of all Italians (54%) making the most likely in Europe to say so. 

Some of the most followed technology-focused social media influencers, like Marques Brownlee and Justine Ezarik hail from the US. Do Americans find tech influencers on social media useful? Roughly half of them (49%) do. 

Half of all Brits (50%) do too. 

On the other hand, respondents in Sweden are most likely (55%) across 17 markets to say social media influencers are not useful sources of tech information, followed by respondents from fellow Nordic market, Denmark (50%). Danes are most likely to say they’re undecided (19%) on whether or not they find tech information from social media influencers useful or not. 

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Methodology: YouGov Surveys: Serviced  provide quick survey results from nationally representative or targeted audiences in multiple markets. The data is based on surveys of adults aged 18+ years in 17 markets with sample sizes varying  between 511 and  2051 for each market. All surveys were conducted online in May 2024. Data from each market uses a nationally representative sample apart from Mexico and India, which use urban representative samples, and Indonesia and Hong Kong, which use online representative samples.  Learn more about YouGov Surveys: Serviced .

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August 10, 2024

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Social media: Disinformation expert offers three safety tips in a time of fake news and dodgy influencers

by Fabrice Lollia, The Conversation

Social networks have revolutionized the way we communicate, stay informed and share moments of our daily lives. We use platforms like Facebook, Twitter, Instagram and TikTok to keep in touch with our friends and family, share our experiences, keep informed, and express our opinions.

But beyond these personal and often superficial uses, social networks play a much more complex and sometimes troubling role in society. The question arises: what impact do social networks have on societal security risk? How can these tools influence or even destabilize society? And how can individual users mitigate the risks?

Societal security risks refer to threats that can undermine the social fabric and stability of a community or nation. These risks often arise from issues such as political instability , economic inequality, social unrest, or large-scale migration. For instance, widespread unemployment can lead to social unrest, jeopardizing societal stability. A more specific example is the spread of misinformation and disinformation. Misinformation is the unintentional spread of falsehoods, while disinformation is the calculated dissemination of lies intended to deceive.

False information circulating through social media and other channels can polarize societies, erode trust in institutions, and incite violence or discrimination.

I study interactions within organizations, with a focus on the impact of new technologies and human dynamics. In a recent article I attempted to answer these questions about the risks that social networks introduce. To do so, I analyzed various aspects of the interactions between social networks and public security. In short, I found that the societal security risk posed by social networks is complex, multifaceted and dynamic. It requires ongoing research, careful regulation and, above all, that all users learn to understand and navigate digital environments critically.

Here, I offer three tips to help individual users minimize the risks of social networks while not losing the benefits:

• build your digital literacy
• avoid algorithmic traps
• be quick to report and block suspicious information or problematic content.

A range of risks

Videos and testimonials shared on social media platforms can help spread the word about events far beyond a single geographical area. Take, for example, the police killing of George Floyd, an African-American man, in 2020. Although the events took place far away, they had a considerable impact in France, where I was living until a few months ago, generating demonstrations of support.

Floyd's death also reignited the debate on police violence and racism in France. These events were taken up by associations defending Black people's rights in France, rapidly creating a phenomenon of transnational solidarity.

The flip side is that sometimes, videos and testimonies can also contribute to the circulation of unverified or even false information, amplifying confusion and anger. Research has shown that fake news spreads six times faster than real information on platforms such as X, formerly called Twitter.

Social networks have also become formidable tools of influence . For example, they allow political leaders and parties to interact directly with their voters, bypass traditional media and control their message by targeting an often young audience.

However, this power to influence can be used maliciously to manipulate information . There is no shortage of examples of disinformation campaigns on platforms such as Twitter or Facebook, whether unfounded rumors, fake accounts or political trolls.

This phenomenon is part of a wider trend of increasing disinformation in Africa : the Africa Center for Strategic Studies reported in March 2024 that "disinformation campaigns seeking to manipulate African information systems have surged nearly fourfold since 2022."

Given that young people are heavy users of these platforms, they become prime targets for misinformation and manipulation.

This is especially worrying since states have increasingly begun to use social networks as a battleground for " information wars ." These battles are fought with true or false information rather than with traditional weapons. They aim to influence public opinion, destabilize political opponents and promote national interests. Electoral interference via social networks has become commonplace, with accusations of orchestrated disinformation campaigns to influence election results.

The potentially dangerous influence of social networks does not stop at politics or misinformation. Online platforms have become fertile ground for spreading extremist rhetoric. This is because they are so easy to access and offer the opportunity to contact individuals directly.

Research shows that extremist organizations have used these platforms to spread their ideologies, often targeting vulnerable young people and exploiting their sense of exclusion or seeking identity. (Social networks are not the only factor in radicalisation—it is a complex process. However, its role should not be ignored.)

Of course, governments and technology companies can make a major contribution to solving these problems. They can work together to develop effective strategies to detect and counter misinformation and disinformation, ensuring that social media platforms remain reliable sources of information and do not become tools for manipulation and deception.

But there is also plenty that individual users can do to make online spaces safer for themselves.

1. Develop your digital literacy: My research has shown that learning how to manage information is a necessary prerequisite for combating disinformation. Users can learn how to critically evaluate and verify information, and how to identify reliable sources. There are initiatives to support this learning, such as WhatsApp's collaboration with the NASSCOM Foundation in India , which aims to train users to spot fake news.

Fact-checking tools and platforms like Libération's CheckNews or Africa Check can be used to verify the accuracy of information circulating online.

2. Avoid algorithmic traps: Be aware of algorithmic biases. I and others have shown that algorithms are never neutral. This is because of inherent biases in their construction and the opaque nature of these systems. These biases can trap users in filter bubbles and promote misinformation to fuel disinformation. It is essential to diversify your sources of information and follow accounts that offer varied perspectives.

3. Don't hesitate to report and block: If you encounter suspicious information or problematic content, use platforms' reporting features to alert moderators. It is also advisable to block persistent sources of disinformation to guard yourself against further exposure.

Provided by The Conversation

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