Optimal Engagement-Diversity Tradeoffs in Social Media

TL;DR

This paper investigates the inherent tradeoff between maximizing user engagement and maintaining opinion diversity on social media platforms, providing theoretical bounds and empirical analysis using Twitter data.

Contribution

It introduces a novel model to quantify the engagement-diversity tradeoff and establishes bounds on maximum engagement under diversity constraints.

Findings

Theoretical bounds on engagement with diversity constraints

Empirical Pareto frontier of engagement and diversity on Twitter

Quantification of worst-case engagement-diversity tradeoff

Abstract

Social media platforms are known to optimize user engagement with the help of algorithms. It is widely understood that this practice gives rise to echo chambers\emdash users are mainly exposed to opinions that are similar to their own. In this paper, we ask whether echo chambers are an inevitable result of high engagement; we address this question in a novel model. Our main theoretical results establish bounds on the maximum engagement achievable under a diversity constraint, for suitable measures of engagement and diversity; we can therefore quantify the worst-case tradeoff between these two objectives. Our empirical results, based on real data from Twitter, chart the Pareto frontier of the engagement-diversity tradeoff.