Influencer Cartels

TL;DR

This paper introduces the concept of influencer cartels as a new market failure in social media advertising, analyzing their effects on consumer welfare through a theoretical model and empirical data analysis.

Contribution

It presents a novel theoretical framework for understanding influencer collusion and empirically investigates influencer cartels using new datasets and machine learning techniques.

Findings

Influencer cartels can increase social media engagement with target audiences.

They may reduce overall consumer welfare by diverting engagement to less relevant audiences.

Policy implications for regulating influencer collusion are discussed.

Abstract

Social media influencers account for a growing share of marketing worldwide. We demonstrate the existence of a novel form of market failure in this advertising market: influencer cartels, where groups of influencers collude to increase their advertising revenue by inflating their engagement. Our theoretical model shows that influencer cartels can improve consumer welfare if they expand social media engagement to the target audience, or reduce welfare if they divert engagement to less relevant audiences. Drawing on the model's insights, we empirically examine influencer cartels using novel datasets and machine learning tools, and derive policy implications.