← 返回论文检索
The ACM Web Conference 2024Research Track: Economics, Online Markets, and Human Computation

Optimal Engagement-Diversity Tradeoffs in Social Media

Fabian Baumann, Daniel Halpern 0002, Ariel D. Procaccia, Iyad Rahwan, Itai Shapira, Manuel Wüthrich

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3589334.3645713 ↗

摘要

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 - 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.