Veniamin Veselovsky

@veniamin.bsky.social

phd student in cs at princeton

New paper in Science: In a platform-independent field experiment, we show that reranking content expressing antidemocratic attitudes and partisan animosity in social media feeds alters affective polarization. 🧵

Today, social media platforms hold the sole power to study the effects of feed-ranking algorithms. We developed a platform-independent method that reranks participants’ feeds in real time and used this method to conduct a preregistered 10-day field experiment with 1256 participants on X during the 2024 US presidential campaign. Our experiment used a large language model to rerank posts that expressed antidemocratic attitudes and partisan animosity (AAPA). Decreasing or increasing AAPA exposure shifted out-party partisan animosity by more than 2 points on a 100-point feeling thermometer, with no detectable differences across party lines, providing causal evidence that exposure to AAPA content alters affective polarization. This work establishes a method to study feed algorithms without requiring platform cooperation, enabling independent evaluation of ranking interventions in naturalistic settings.

New paper: Do social media algorithms shape affective polarization? We ran a field experiment on X/Twitter (N=1,256) using LLMs to rerank content in real-time, adjusting exposure to polarizing posts. Result: Algorithmic ranking impacts feelings toward the political outgroup! 🧵⬇️

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Excited to finally share work from this summer! We propose using structured negotiation games to evaluate language models. LMs are being used to create *dynamic* agents but benchmarks have remained *static*. Structured negotiation games solve this!

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I’m hitting the job market looking mainly for tenure-track asst. professor positions (2024)!  My core research informs how we should curate content on online platforms — and I’m also interested in how large language models will impact on the Web in the upcoming years.