Call for Submissions: AI for Social Science Methodology (Yale)
• Keynote: @nachristakis.bsky.social
• Panel with editors of leading journals on publishing AI research
• Mentoring roundtables for early-career scholars
• Generous travel support
Discussion-driven, high-quality research.
Recently, van der Stigchel and colleagues posted a provocative commentary suggesting that we should be wary of bots in online behavioral data collection (🧵by @cstrauch.bsky.social here: bsky.app/profile/cstr...). But should we? Here is my response letter osf.io/preprints/ps.... 1/5
Great write-up on our recent studies:
“Back in the day, if you wanted to know what the Seattle General Strike was, you’d grab an encyclopedia or ... check Wikipedia,” Karell said. “Now, you just ask ChatGPT... Increasingly, the information we rely on is being packaged by tools built by companies.”
Our new paper is out today in @pnasnexus.org with colleagues at Yale (@matthewshu.com, Danny Karell, @keitarookura.bsky.social)
We wanted to understand how using AI-generated summaries to learn about history influenced attitudes compared to existing resources like Wikipedia. 1/4
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
Robustness checks showed that GPT-4o tended to generate liberal-leaning summaries across a wide range of historical events, highlighting the importance of default biases.
More work is needed to understand how these patterns might generalize to other topics and across different models. 4/4
This helps distinguish between two pathways of AI influence: latent biases baked into models from training, and prompting biases introduced through deliberate prompting. Both can shape opinions even when the content is factually accurate. 3/4
Paper: academic.oup.com/pnasnexus/ar...
We ran an experiment where people read GPT-4o summaries or Wikipedia.
Default summaries with no ideological slant and texts generated using a liberal persona both shifted readers toward liberal opinions relative to Wikipedia.
Conservative-framed texts only shifted among conservatives. 2/4
Our new paper is out today in @pnasnexus.org with colleagues at Yale (@matthewshu.com, Danny Karell, @keitarookura.bsky.social)
We wanted to understand how using AI-generated summaries to learn about history influenced attitudes compared to existing resources like Wikipedia. 1/4
a gpt in a sublime 200 lines of pure Python — it is all there. Incredible for teaching students (and yourself)
karpathy.github.io/2026/02/12/m...
Come work w CSMaP!
We're hiring two postdocs.: one with a focus on AI; other is general focus.
Let me know if you have questions about the roles. And please share widely.
apply.interfolio.com/181817
apply.interfolio.com/181820
Benchmarks of LLM common sense overwhelmingly rely on correct labels to report an accuracy score. But what if your "ground truth" genuinely differs from mine?
In a new @pnasnexus.org paper, @duncanjwatts.bsky.social, @whiting.me and I explore the implications of this intriguing question.
🧵⤵️
📢WORK! At the Sociology department of @utrechtuniversity.bsky.social we are hiring a postdoc who will work on applications of AI in sociological research. Join our vibrant-yet-cohesive research community doing cutting-edge research. Please share or apply! www.uu.nl/en/organisat...
AI does not engage in motivated reasoning
While individuals processing information may be motivated to
reach a certain conclusion, LLMs have no such motivation and operate on purely cognitive input. As such, they do not mimic humans in motivated reasoning tasks.
arxiv.org/pdf/2601.16130
LLMs are very good at extracting information from academic articles. They are much better than even highly trained humans (our grad RAs had hundreds of hours of practice). And of course they're ~1000x cheaper and faster
Really interesting new paper from some of my former @gesis.org colleagues in @bigdatasoc.bsky.social: "From (almost) open to heavily restricted data access – The development of the Twitter/X developer policies"
doi.org/10.1177/2053...
#commsky #computationalsocialscience
Screen shot of title page of a preprint. Title: Should generative AI be used in reflexive qualitative research? Authors: Elida Izani Ibrahim, Laura K. Nelson, and Andrea Voyer
Recent publications arguing against the use of genAI in reflexive qual research inspired us (Elida Ibrahim and @andreavoyer.bsky.social) to write our own perspective. Not to convince anyone to use genAI but for those who might be interested and are looking for guidance.
osf.io/preprints/so...
Last week the story was that TikTok censored anti-Trump/ICE/Pretti videos after the U.S. ownership change. We investigated with a large set of US TikTok data and found some interesting results, short thread...
First 50 downloads are free if you use this link: www.tandfonline.com/eprint/AYC6H...
New paper examines the relationship between online political discourse and structural conditions.
European parties responded to national asylum numbers by increasing online attention, but content differed. Left-wing parties posted more in solidarity and right-wing parties shared more about crime.
Hey sociologists, I'm organizing an ASA Methodology session on AI! Submissions are due by 2/25. Looking forward to a timely cross-method convo on emerging research best practices and disciplinary norms and ethics in August.
Very interesting research paper that shows that using AI with programming can significantly reduce mastery over topics. Perhaps unsurprising, but the lack of significant speed gains in this exercise are remarkable
www.anthropic.com/research/AI-...
Now out in Sociological Science
(How) do sociologists use GenAI for their research? Find out in our paper.
Written with @ajalvero.bsky.social @dustinstoltz.com and Marshall Taylor. Thank you to everyone who participated in the survey!!
We just published the methodology behind CoPE, our 9B parameter model that matches GPT-4o at content classification at 1% the size! The model is already open source, but now we're sharing our training technique. blog.zentropi.ai/how-we-built... 🧵 1/6
On the topic of AI and social science research, the Research Briefing on my Nature Human Behaviour paper is now online. It's an accessible summary of the research, implications, and some behind-the-scenes commentary.
Thanks @gligoric.bsky.social for providing an expert opinion!
Particularly if academics block each other for engaging in legitimate discussions about contested issues
On the consent front, I think the use of LLMs to create more bespoke, even "individualized" instruments raises new ethical questions that warrant discussion. Seeing how polarizing the topic has become, I expect we'll see a lot more acrimonious debate before any consensus emerges
Putting informed consent aside, there is a strong minimal risk argument for using LLMs to analyze publicly available documents (particularly open-access published research), given that such materials are already routinely ingested by LLMs, with and without researcher intervention.
New paper in Social Science Computer Review 🚨
We conducted two experiments to understand the effects of reading AI summaries, focusing on historical events 📜🤖👩💻
We found that AI improved factual recall, possibly due to post-training optimization
journals.sagepub.com/doi/10.1177/...
