Optimal Engagement-Diversity Tradeoffs in Social Media
Name
3589334.3645713.pdf
Size
1.25 MB
Format
Adobe PDF
Checksum (MD5)
041b90a692d0cb3deacb7b92d6eac310
Author(s)
Baumann, Fabian
Halpern, Daniel
Procaccia, Ariel D.
Rahwan, Iyad
Shapira, Itai
Wüthrich, Manuel
Date Issued
May 13, 2024
Publisher
ACM
Citation
Baumann, Fabian, Halpern, Daniel, Procaccia, Ariel D., Rahwan, Iyad, Shapira, Itai et al. 2024. "Optimal Engagement-Diversity Tradeoffs in Social Media."
Version
Final published version
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 - 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.
Description
WWW '24: Proceedings of the ACM on Web Conference May 13–17, 2024, Singapore, Singapore
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3589334.3645713
