Assistant Professor of Sociology @RutgersU | Computational social science, politics, and AI

Joined October 2016
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New paper in Nature Human Behaviour. I use a conjoint experiment to evaluate the capabilities of the latest models for context-sensitive moderation and compare the results with those from human subjects, demonstrating how social science techniques can enhance AI auditing. πŸ’»πŸ€–πŸ’¬
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Thomas Davidson retweeted
πŸ“’ Call for Reviewers: WOAH @ #EMNLP2026 WOAH is looking for reviewers to help evaluate submissions for our 10th edition at EMNLP 2026. Interested in serving as a reviewer? πŸ”— docs.google.com/forms/d/e/1F… Thank you for helping us make #WOAH2026 a success! #NLP #AI #OnlineSafety
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Thomas Davidson retweeted
✨New paper out @SpringerNature✨ For 8 weeks around the 2024 US election, we randomly assigned 2,000 people to use social media algos we custom-built. Do engagement-based algorithms amplify intergroup, moral & emotional content does that distort how we see political norms? 🧡
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Mercor has some interesting opportunities for getting involved in evaluating frontier AI models. I have found it an insightful experience, and you can get paid for helping to make AI less sloppy! Happy to chat if anyone has questions. t.mercor.com/y6A4l

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🚨 Update: WOAH Mentorship @ #EMNLP2026 🚨 Deadline extended to April 17! πŸ“… Still time to apply as mentor or mentee and develop your WOAH submission with expert guidance πŸ’‘ πŸ“ Mentor: forms.gle/XaK8KBFomaWZZwG98 πŸ“ Mentee: forms.gle/AC5akVcdzsCvwqEo7 Join us! 🌍 #NLP #WOAH
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Mar 10
πŸ“’ Applications Open! Join the 2026 Summer Academy on Large Language Models for Social Science at Columbia University πŸ—“ May 26 – June 5, 2026 πŸ“… Apply by March 20, 2026 #LLM #SocialScience #AIResearch #ComputationalSocialScience #NLP
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AI-generated summaries of history led to more liberal opinions compared to Wikipedia, while summaries by chatbots prompted to use a conservative framing produced more conservative opinionsβ€”but primarily among conservative readers. In PNAS Nexus: ow.ly/oYQH50YpOHO
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Thomas Davidson retweeted
Call for Submissions: AI for Social Science Methodology @yaledatascience β€’ Keynote: @NAChristakis β€’ Panel with editors of leading journals on publishing AI research β€’ Mentoring roundtables for early-career scholars β€’ Generous travel support Discussion-driven, high-quality research. πŸ“© Submit your work: yalefds.swoogo.com/socialsci… Please share with colleagues working at the AI Γ— social science frontier! @Yale @PopAssocAmerica
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Thomas Davidson retweeted
Want to learn about computational social science *for free* and identify new research partners across academic fields? Apply to one of the 2026 Summer Institutes in Computational Social Science (described in yellow in the attached map) here: sicss.io/locations
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Thomas Davidson retweeted
New paper in Nature Human Behaviour. I use a conjoint experiment to evaluate the capabilities of the latest models for context-sensitive moderation and compare the results with those from human subjects, demonstrating how social science techniques can enhance AI auditing. πŸ’»πŸ€–πŸ’¬
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Thomas Davidson retweeted
Article by @thomasrdavidson examines how multimodal LLMs evaluate hate speech: larger models aligned with human judgment in context-sensitive decisions, but pervasive demographic and lexical biases remain, and visual identity cues may amplify disparities. nature.com/articles/s41562-0…

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New paper in Nature Human Behaviour. I use a conjoint experiment to evaluate the capabilities of the latest models for context-sensitive moderation and compare the results with those from human subjects, demonstrating how social science techniques can enhance AI auditing. πŸ’»πŸ€–πŸ’¬
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Overall, these results show that MLLMs can make more context-sensitive moderation decisions than text-based classifiers. These systems still make mistakes, and context can cut both ways, eliminating some biases while enabling others. Human oversight thus remains essential.
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The paper is out now: nature.com/articles/s41562-0… You can read it without a paywall using this guest link: rdcu.be/eUIlm

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I'm recruiting multiple PhD students for Fall 2026 in Computer Science at @JHUCompSci πŸ‚ Apply to work on AI for social sciences/human behavior, social NLP, and LLMs for real-world applied domains you're passionate about! Learn more kristinagligoric.com/ & help spread the word!
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Thomas Davidson retweeted
Happy to announce the 2025-2026 @UTM @UTMsoc Speaker Series @UofT @UofTNews @LucaMPesando @MarotoMichelle @thomasrdavidson
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Thomas Davidson retweeted
Should WOAH start a mentorship programme? πŸ€” As the workshop grows, reviewer expectations are rising. We don’t want contributors from adjacent communities penalised by *CL norms. Senior PhDs and beyond could be mentors. Share your thoughts: πŸ‘‰ forms.gle/safif3rU2rs5S6H88
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New pre-print on large reasoning models πŸš¨πŸ€–πŸ§  To what extent does LRM behavior resemble human reasoning processes? I find that LRM reasoning effort predicts human decision time on pairwise comparison tasks, and that both humans and LRMs use more time/effort on harder tasks
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Analysis of the reasoning traces for Gemini 2.5 shows that the model emphasizes second-order factors when faced with such decisions, helping to avoid common false positives like flagging reclaimed slurs as hate speech.
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There are, of course, caveats: LRMs do not replicate human cognition, there are limits to their capabilities, and reasoning is not always faithful Check out the preprint and feel free to share any feedback: arxiv.org/pdf/2508.20262

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