brands Archives - Grady College

Alex Pfeuffer, Haley Hatfield (Ph.D. student), & Jooyoung Kim. “Will Brands Make it if They Fake it? Exploring the Effects of CGI Influencer Disclosures in Sponsored Social Media Posts.” Paper to be presented at the American Academy of Advertising Annual Conference 2023 in Denver, CO.

Abstract: CGI (computer-generated imagery) influencers have become a popular tool for brands to promote their products, as they can be made to look, act, and communicate as brands please. However, CGI influencers’ existence has prompted questions and concerns among consumer protection advocates and regulators, as these virtual influencers cannot always be readily discerned from their human counterparts, and their profiles can reflect unrealistic or inhuman body proportions. Consumers may be misled if they do not know that an influencer endorsing a product is not human and experience harmful effects if they compare themselves to unattainable beauty standards. While regulatory approaches exist in some countries to require disclosure for edited and manipulated images on social media posts, the practice of computer-generating influencers does not require disclosure. The present study draws on the theoretical frameworks of persuasion knowledge and Signaling Theory as well as the theoretical construct of trust to examine the effects of CGI influencer disclosures. Results show that such disclosures hold the potential to activate consumers’ persuasion knowledge and reduce body comparison, but also lead to less favorable perceptions regarding the influencer and brand. Implications for various stakeholders, including scholars, regulators, brands, and content creators are discussed.

Abstract: In the current highly fragmented (social) media landscape, brands must increasingly rely on their own consumers to reach out to new potential consumers. Taking a social networks approach, the current study examines patterns of consumer engagement with brands on social media, identifying the major clusters as well as key users and messages that are responsible for cross- clusters engagement and information flow. After identifying these clusters, we employ large-scale automated content and image analysis to (a) identify the social mediators, and (b) the content characteristics (i.e., media richness, concepts expressed & brand emphasis in images) and sentiment of messages that cut through clusters. Our initial findings suggest that content that gets mediated across clusters is generally less marketer-driven and less polished than traditional advertising, possibly grassroots-style. These results highlight the novelty, feasibility and value of the proposed approach to explaining brand-related content flow across clusters.