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How Instagram Algorithms Can Impact Influencer Following and Endorsement Effectiveness

We’ve all heard the old rhetorical question about our friends and jumping off of bridges, but here’s a new one for the era of social media: if all of your friends followed influencers on Instagram, would you follow them too?

Probably, as it turns out.

Influencers – individuals who “cultivate celebrity capital on social media by crafting an authentic personal brand” – have become big business in a short period of time, reaching a market value of over $13 billion in 2022. They also make up a large portion of the content on some social media sites, particularly Instagram.

Many social media platforms, including Instagram, use algorithms to put content in front of consumers. This does more than just curate a content list, it also gives cues to users about what content is considered useful or popular, and what content other people are following. Over time, this has the potential to create a behavioral norm, or a “perception of which behaviors are typically performed.”  As users see more and more influencer content, it can create a sense that many others must be following influencers since the content is so prevalent. Thus, a behavioral norm of following influencer content is established, centering it as a normal, useful action.

Researchers Yang Feng, University of Florida College of Journalism and Communications Associate Professor in Artificial Intelligence, and Quan Xie, Southern Methodist University Temerlin Advertising Institute Professor of Advertising, sought to understand the potential link between the perceived behavioral norm of following influencers on Instagram (which they term the influencer following norm) and the effectiveness of influencer marketing on the platform. To do this, they tested a complex model suggesting that influencer following norms were a starting point that could eventually lead to product purchasing intentions.

Study results confirmed that while merely using Instagram wasn’t enough to create a sense of influencer following norms, being exposed to algorithmically suggested content was. Notably, these norms were able to predict categories of gratification, which in turn were able to also predict increases in the appraisal of influencer personal characteristics.

The research showed that the development of a behavioral norm around following influencers was clearly impactful – these norms drove use gratifications, which in turn influenced perceptions of the influencer, which in turn influenced perceptions of the product, which in turn influenced purchase intentions,

The study provides important insight for influencers. By decomposing several types of audience gratifications and showing their links to different kinds of characteristics, this work gives influencers a framework for enhancing their credibility in ways that matter most for their audiences. Additionally, this research suggests that when it comes to influencer marketing, there may not be such a thing as too much, with those exposed to the most influencer content via the algorithmic platform environment also being more likely to follow that content. It might make most sense, then, for those planning influencer marketing campaigns to target the heaviest users, and to tailor that marketing content to align with the most impactful audience gratifications while they’re at it.

The original article, “Influencer Marketing in Web 3.0: How Algorithm-Related Influencer following Norms Affect Influencer Endorsement Effectiveness,” was published online in the Journal or Promotion Management on Nov. 12, 2023.

Authors: Yang Feng, Quan Xie

This research was summarized by Vaughan James, Ph.D.

Posted: January 29, 2024
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