A new study has found that consumers’ exposure to algorithmic social media can affect their purchase intentions of products endorsed by influencers.

The findings by Yang Feng, University of Florida College of Journalism and Communications (UFCJC) Advertising associate professor in artificial intelligence, and Southern Methodist University Assistant Professor Quan Xie are featured in “Influencer Marketing in Web 3.0: How Algorithm-Related Influencer following Norms Affect Influencer Endorsement Effectiveness” published online in the Journal of Promotion Management on Nov. 12, 2023.

The authors explored the relationship between algorithm-related influencer following norms and influencer marketing effectiveness. Influencer following norms refers to the phenomenon in which Instagram’s algorithm often shows users influencer posts that have a lot of likes, and this makes users think that following these influencers is something many other people do.

The researchers “found that people’s influencer following norms played a significant role in shaping influencer endorsement effectiveness (e.g. influencer following gratifications, perceived influencer characteristics, and effectiveness of influencer product recommendation). Moreover, people’s exposure to the algorithmic social media environment (i.e. suggested and top posts provided by Instagram’s recommendation algorithms) is related to their perceived influencer following norms.”

They add, “Overall, our results indicated that consumers’ exposure to the algorithmic social media environment affected their purchase intentions of products endorsed by influencers via perceived influencer following norms, influencer following gratifications, and perceived influencer characteristics.”

Posted: November 14, 2023
Category: AI at CJC News, College News
Tagged as: Advertising, Algorithm-Relater Influencer Followin Norms, Influencer Marketing, Social Media, Yang Feng