6 papers
From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes
Rubén Garzón, Pauline Baron, Vincent Grari +3
Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demographics, for example country,…
The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement
Jonathan Stray, Ian Baker, George Beknazar-Yuzbashev +42
We report the first direct comparisons of multiple alternative social media algorithms on multiple platforms on outcomes of societal interest. We used a browser extension to modify…
Whose Values? Measuring the (Subjective) Expression of Basic Human Values in Social Media
Ziv Epstein, Farnaz Jahanbakhsh, Tiziano Piccardi +4
The value alignment of sociotechnical systems has become a central debate, but progress depends on how human values are perceived in the content these systems surface and how such…
Reranking Social Media Feeds: A Practical Guide for Field Experiments
Tiziano Piccardi, Martin Saveski, Chenyan Jia +3
Social media plays a central role in shaping public opinion and behavior, yet performing experiments on these platforms and, in particular, on feed algorithms is becoming increasin…
Reranking partisan animosity in algorithmic social media feeds alters affective polarization
Tiziano Piccardi, Martin Saveski, Chenyan Jia +3
Today, social media platforms hold sole power to study the effects of feed ranking algorithms. We developed a platform-independent method that reranks participants' feeds in real-t…
Alexandria: A Library of Pluralistic Values for Realtime Re-Ranking of Social Media Feeds
Akaash Kolluri, Renn Su, Farnaz Jahanbakhsh +3
Social media feed ranking algorithms fail when they too narrowly focus on engagement as their objective. The literature has asserted a wide variety of values that these algorithms…