New📄(accepted at #ACL2026NLP main):
W&C-Sent: 1.6k+ English sentences from social media labeled for perceived warmth (trust, sociability) & competence toward individuals and target groups (key for studying stereotypes, biased lgge, & other #NLP and #CSS applications).
arxiv.org/abs/2601.06316
fresh off the press from yours truly: oecs.mit.edu/pub/b61joemo...
I offer an overview of algorithmic bias. I trace its historical roots, examine canonical scholarship and notable real-world incidents, and explore how algorithmic bias emerged as a field of study
1/
Chapter 7: @kwelle.bsky.social of @gesis.org & @indiiigo.bsky.social of Mannheim on using social media data in CSS. Social media provides rich digital traces of human behavior, but also raises serious methodological & ethical challenges, from platform bias to reproducibility. A great guide!
Are you using survey-style questionnaires designed for humans to measure characteristics of LLMs?
In our #EACL2026 paper, we evaluate both the reliability and validity of such tests and found that their scores do not reflect real-world model behavior. In fact, they can be deceptive!
🧵1/3
An image of the schedule with speaker images. You can find the full schedule on tada.cool.
🚨 TADA Speaker Series Spring 2026 schedule is here! 🚨
We've assembled a fantastic lineup of researchers exploring the future of survey research in the age of LLMs.
Mar 18 - May 27, online at 17:00 CEST. Join us!
More info & signup: tada.cool
Illustration of two people standing indoors, each holding a laptop facing the other. Files appear to transfer between their screens through floating folders and documents arcing from one computer to the other. A couch, hanging lights, window, and potted plant are visible in the background.
📢 Last call for abstracts!
Submit your work to the DACH-CSS Conference 2026, May 21–22 in Vienna, hosted by CSH & CEU.
Accepted abstracts: 3-minute talk + poster session.
🗓 Deadline: TODAY (Feb 20)
📝 Registration open
Details: computational-social-science.org/workshops/20...
#CSS #DACH #Vienna
Can feed algorithms shape what people think about politics? Our paper "The Political Effects of X's Feed Algorithm" is out today in Nature and answers "Yes."
www.nature.com/articles/s41...
Announcing our latest paper: CommonLID
In collaboration with @commoncrawl.bsky.social @mlcommons.org @jhu.edu we built a LID benchmark on actual Common Crawl text covering 109 languages. Existing evaluations overestimate how well LangID works on web data.
arxiv.org/abs/2601.18026
cool, my fellow colleagues @kwelle.bsky.social and @indiiigo.bsky.social also contributed a chapter www.elgaronline.com/edcollchap/b...
We're excited about the next edition of our Summer School for Women* in Political Methodology, this time organized by the 💫 local team in Mannheim!
#cometoGESIS #workwithus #Gastforschungsaufenthalt #researchvisit
We invite Ph.D. students and early career postdocs to come to GESIS. Visiting researchers of the Junior Research Program are involved in our research to publish with GESIS staff, and to develop research ideas and joint projects.
Paper accepted to #EACL2026 main conference 🎉
@taniseceron.bsky.social, Sebastian Padó and I test multilingual LLMs before and after English-only fine-tuning and find strong cross-lingual political opinion transfer across five Western languages.
www.arxiv.org/abs/2508.05553
Demographic cues (eg, names, dialect) are widely used to study how LLM behavior may change depending on user demographics. Such cues are often assumed interchangeable.
🚨 We show they are not: different cues yield different model behavior for the same group and different conclusions on LLM bias. 🧵👇
I had the absolute pleasure to visit @craicexeter.bsky.social, where I laid out an argument for how critical & computational scholars should lead the conversation on AI. We need to expand research on harms, interrogate corporate hype, and support people’s critical understanding these technologies
I missed this last month from @tilmanbayer.bsky.social: "AI finds errors in 90% of October's Featured Articles". Great example of human-in-the-loop LLM use for verifying Wikipedia articles. en.wikipedia.org/wiki/Wikiped...
Many think LLM-simulated participants can transform behavioral science. But there's been a lack of accessible discussion of what it means to validate LLMs for behavioral scientists. Under what conditions can we trust LLMs to learn about human parameters? Our paper maps the validation landscape.
1/
Most LLM evals use API calls or offline inference, testing models in a memory-less silo. Our new Patterns paper shows this misses how LLMs actually behave in real user interfaces, where personalization and interaction history shape responses: arxiv.org/abs/2509.19364
It's out!!
www.science.org/doi/10.1126/...
Big thank you to my coauthors @small-schulz.bsky.social and @lorenzspreen.bsky.social, and to all participants who discussed 20 political issues over 4 weeks in 6 subreddit, 3 experimental conditions and let us observe.
The Center for Information Technology Policy at Princeton invites applications for a Postdoctoral Fellow to work with Andy Guess (Politics/SPIA), Brandon Stewart (Sociology), and me (CS).
puwebp.princeton.edu/AcadHire/app...
Please apply before Sunday, the 13th of December!
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 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.
🧵
Preprint alert! 🥳
How are social bias and CSS interconnected? 🤔
@aytalina.bsky.social, @janabernhard.bsky.social, @valeriehase.bsky.social, and I argue that social bias shapes CSS as a field and as a methodology. Progress in CSS depends on engaging with both dimensions! osf.io/preprints/so...
🌍 Are you new to @icwsm.bsky.social or JQD:DM
and based in a low- or middle-income country?
💡 Submit a project idea, get matched with a mentor, present virtually at ICWSM'26, and prepare a submission for Sept 2026!
📢 Call icwsm.org/2026/submit....
🚀 Apply by Jan 15 forms.gle/A9GkJboP7qi3...
🚨 I'm recruiting PhD students in Computer Science at Johns Hopkins University for Fall 2026. If you're interested in AI, HCI, and designing better online platforms and experiences, apply to work with me!
More info: piccardi.me
📢 New insights on #GenAI interviewing agents asking sensitive open questions compared to a text-based web survey.
Answers to male agent include more topics, but no evidence of social desirability.
👉 New #OpenAccess paper with @jkhoehne.bsky.social #cneuert in #IJMR.
🌐 doi.org/10.1177/1470...
⏳ Only 5 days left to apply!
Please note the updated application link (due to a recent university webpage update):
👉 PhD Candidate in Emotionally and Socially Aware Natural Language Processing
careers.universiteitleiden.nl/job/PhD-Cand...
A staircase in the new School of Computer, Data & Information Sciences building at Wisconsin Madison. Tan wood structures surround tapestry art and a small indoor garden.
A view from above of the staircases in the Wisconsin CDIS building
An shot from below of winding wooden staircases and a glass atrium rooftop. The new School of Computer, Data & Information Sciences building at Wisconsin Madison.
A bicolor white cat with seal-colored markings, looking upwards with big wide dark eyes.
It's the season for PhD apps!! 🥧 🦃 ☃️ ❄️
Apply to Wisconsin CS to research
- Societal impact of AI
- NLP ←→ CSS and cultural analytics
- Computational sociolinguistics
- Human-AI interaction
- Culturally competent and inclusive NLP
with me!
lucy3.github.io/prospective-...
Join our CSS department @gesis.org! Postdoc/senior researcher position, tenure track! All info at: www.gesis.org/institut/kar...
Misinformation research has a causality problem: lab experiments are limited; observational studies confounded.
We used causal inference on 9.9M tweets, quantifying effects in the wild while blocking backdoor paths.
Does misinfo get higher engagement? Are following discussions more emotional? 🧵
That sounds rough and I feel the same sometimes (hopefully most academics do, especially when starting out?). I hope you got some constructive feedback for future sessions.
