Assistant Professor of Sociology | Computational social science, politics, and AI
Chapel Hill, NC
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. 💻🤖💬
Thomas Davidson retweeted
📢 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?
🔗 docs.google.com/forms/d/e/1F…
Thank you for helping us make #WOAH2026 a success!
#NLP #AI #OnlineSafety
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? 🧵
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
Thomas Davidson retweeted
🚨 Update: WOAH Mentorship @ #EMNLP2026 🚨
Deadline extended to April 17! 📅
Still time to apply as mentor or mentee and develop your WOAH submission with expert guidance 💡
📝 Mentor: forms.gle/XaK8KBFomaWZZwG98
📝 Mentee: forms.gle/AC5akVcdzsCvwqEo7
Join us! 🌍 #NLP #WOAH
Thomas Davidson retweeted
📢 Applications Open!
Join the 2026 Summer Academy on Large Language Models for Social Science at Columbia University
🗓 May 26 – June 5, 2026
📅 Apply by March 20, 2026
#LLM #SocialScience #AIResearch #ComputationalSocialScience #NLP
Thomas Davidson retweeted
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 opinions—but primarily among conservative readers. In PNAS Nexus: ow.ly/oYQH50YpOHO
ALT General strike participants leaving shipyards, Seattle, February 1919. This image of workers was taken at the Skinner & Eddy Corporation shipyard located between Dearborn Street and Connecticut Street (now Royal Brougham Way). The nitrate photo shows signs of deterioration on some light parts of the image.
Thomas Davidson retweeted
Call for Submissions: AI for Social Science Methodology @yaledatascience
• Keynote: @NAChristakis
• Panel with editors of leading journals on publishing AI research
• Mentoring roundtables for early-career scholars
• Generous travel support
Discussion-driven, high-quality research.
📩 Submit your work:
yalefds.swoogo.com/socialsci…
Please share with colleagues working at the AI × social science frontier! @Yale @PopAssocAmerica
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
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. 💻🤖💬
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…
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.
The paper is out now: nature.com/articles/s41562-0…
You can read it without a paywall using this guest link: rdcu.be/eUIlm
Thomas Davidson retweeted
I'm recruiting multiple PhD students for Fall 2026 in Computer Science at @JHUCompSci 🍂
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!
Thomas Davidson retweeted
Happy to announce the 2025-2026
@UTM @UTMsoc Speaker Series @UofT @UofTNews @LucaMPesando @MarotoMichelle @thomasrdavidson
Thomas Davidson retweeted
Should WOAH start a mentorship programme? 🤔
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:
👉 forms.gle/safif3rU2rs5S6H88
New pre-print on large reasoning models 🚨🤖🧠
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
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.
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