Chapter 17: Andreas Flache @mrnkzr.bsky.social & Michael Mäs on Agent-Based Models & Networks. A thoughtful chapter arguing that computational social science needs both large-scale empirical & and mechanism-based simulations to explain how individual interactions produce collective phenomena.

Today marks the beginning of Ireland's EU Presidency! Watch our video series 'Ireland as EU President' at the link below & see what Ireland can bring to the table over the next six months. www.tcd.ie/ssp/research... @tahayasseri.bsky.social @farbod-a.bsky.social @tcdeconomics.bsky.social

Chapter 16: Stephanie Zonszein, PM Aronow, & @cdsamii.bsky.social on estimating causal effects in the presence of network spillovers. A clear introduction to one of the key methodological challenges in CSS: how to identify causal effects when one person's treatment changes someone else's outcome.

Can Ireland keep AI under control?🧐 In our final video of the 'Ireland as EU President' series, Professor @tahayasseri.bsky.social explains why Ireland is the perfect candidate for steering the future of AI regulation in Europe 👇 @tcdsociology.bsky.social @tcddublin.bsky.social

💥New | Gendered AI design reflects and reinforces society’s biases ✍️ @tahayasseri.bsky.social & @cuihaosabrina.bsky.social #Sociology #AI #GenderedDesign

Many are familiar with Friendship Paradox (“your friends are more popular than you, on average “). But did you know FP holds when you swap mean for the median? Yes, MOST friends are more popular than you. This opens networks up to some mind blowing consequences

Chapter 15: @kristinalerman.bsky.social on the Strong Friendship Paradox. Showing how the structure of social networks systematically biases our perceptions of reality. When our friends are not representative of the population, rare behaviours and opinions can appear surprisingly common.

Chapter 14: @bolozna.bsky.social on multilayer social networks. A great introduction to one of the most important recent developments in network science: moving beyond single-layer graphs to represent the multiple social contexts and relationships that shape human behavior. Social life is layered!

Chapter 13: @jsaramak.bsky.social & @pholme.bsky.social on temporal networks of social interactions. A fascinating chapter showing why static network snapshots often miss the most important thing: the timing and order of interactions. Social networks are dynamic processes, not just fixed structures.

Who'd have thought Grokipedia had a rightward political bias — especially on pages about religion, history, and literature and art? 🤔 And as a bonus, it is harder to read! The analyzed Grokipedia articles in this study were more wordy, complex, and contained fewer references per word.

Selective divergence between Grokipedia and Wikipedia articles www.pnas.org/doi/abs/10.1...

Professor @tahayasseri.bsky.social and PhD candidate Saeedeh Mohammadi have published new research on Grokipedia and its structural biases. 🗣️ ✍️Read the article: www.pnas.org/doi/10.1073/... @tcdschoolssp.bsky.social @soham-centre.bsky.social

A large-scale analysis of Grokipedia, the world’s first AI-written encyclopedia, found that Grokipedia selectively draws on more right-leaning news sources. The study was conducted by Saeedeh Mohammadi and @tahayasseri.bsky.social at @soham-centre.bsky.social. See link to full press release ⬇️

Kicking off day 2 of Machine+Behavior: @tahayasseri.bsky.social moderating a discussion with speakers Kinga Makovi and Eric Schulz.

Paper out in @pnas.org We compared ~18,000 matched articles between Wikipedia and Grokipedia, xAI’s AI-generated encyclopedia. While many pages closely mirrored Wikipedia, a substantial subset diverged markedly in content, sourcing, and political orientation, especially in religion and history.

Paper out in @pnas.org We compared ~18,000 matched articles between Wikipedia and Grokipedia, xAI’s AI-generated encyclopedia. While many pages closely mirrored Wikipedia, a substantial subset diverged markedly in content, sourcing, and political orientation, especially in religion and history.

Chapter 12: @fedebotta.bsky.social from @exetercompsci.bsky.social on online images and computational social science. A fascinating chapter on how images shared online can help us study politics, misinformation, culture, & collective behaviour and why visual data deserves a much bigger place in CSS.

Chapter 11: Luis-Daniel Ibáñez, Johanna Walker & @elenasimperl.bsky.social on open data in computational social science. Why open data is not just a technical issue, but also a question of sustainability, impact, politics, and bias. Useful data is more than available data. @aiatkings.bsky.social

Chapter 10: @feloe.bsky.social & @vanatteveldt.com on social media data donation and digital tracking. A very useful chapter on how digital traces can be integrated into social science research, not as a replacement for surveys and other methods, but as a powerful complement.

Join us on Thursday, 30 April, at 14:30 CET for the International Roundtable on Computational Social Science with @tahayasseri.bsky.social 🔹 A New Sociology of Humans and Machines 🔹 More info: liu.se/en/event/int...

We are delighted to announce an ONLINE Information Session for our MPhil in Race, Ethnicity and Conflict. 💫 📅 Thurs, 23 April ⏰ 3pm 💻 via Zoom Register via: tcd-ie.zoom.us/meeting/regi... @tcdschoolssp.bsky.social

Chapter 9: Kiran Garimella on using WhatsApp data for computational social science. An important chapter on why WhatsApp deserves far more attention in CSS, not only because of its scale, but because it opens a window onto digital life beyond the usual Western, open-platform focus.

As AI systems take on managerial roles, do human biases follow? Fair AI isn’t just a technical problem — it’s a human one. Read our new research with @tahayasseri.bsky.social @soham-centre.bsky.social ⬇️ lnkd.in/e3idgSZk

Chpater 8: @dirkhovy.bsky.social, M Gerondeau & J Globisz on text data and natural language processing. A very useful chapter on why text is such a rich source for CSS, and how NLP can help with exploration, prediction, and generation; if used thoughtfully and with clear research goals.

Delighted to host the inaugural lecture of the etc. Series Dr. Rilla Khaled, Director of @tag-centre.bsky.social & Associate Professor at @concordia.ca, will speak on “Real (talk) > True (talk): Making space for making”, reflecting on nearly a decade of work on design practice and research.

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!

Same decision, different judgment. If people project the same gender biases onto AI managers, what does that suggest about our future interactions with AI? Read our work ⬇️ doi.org/10.1016/j.ch... @tahayasseri.bsky.social @soham-centre.bsky.social @tcdsociology.bsky.social

Our Researcher of the week is @ucddublin.bsky.social #PhD #Student Faezeh Fadaei. Faezeh's work is on "Gender Dynamics and Homophily in a Social Network of LLM Agents" Check out Faezeh's video: vimeo.com/1167656753 @researchireland.ie @tahayasseri.bsky.social

New preprint with Ruiqing (Rachel) Han & @cuihaosabrina.bsky.social on how people evaluate AI managers. One finding surprised us: adding a face shifts evaluation from performance to social perception. Take note AI system designers: interface choices are not neutral. @tcdsociology.bsky.social

Chapter 6: @lauraknelson.bsky.social from UBC Sociology on computational inductive research. The chapter makes a strong case that unsupervised methods don’t replace theory: they reshape how we generate & validate it. Induction, abduction, deduction, combined with transparency & reproducibility.

Chapter 5: @martinarvidsson.bsky.social, Hedström, Jarvis & @marckeuschnigg.bsky.social on the intersection of Analytical Sociology and Computational Social Science. Computational tools are most powerful when used to identify and test mechanisms, not just describe or predict aggregate patterns.

In Chapter 4, Ralph Schroeder of @oii.ox.ac.uk argues that CSS needs a stronger theory, not just better data. He proposes an AI-driven model of media agenda-setting that links media visibility, public attention, and political change. A big step toward cumulative media theory.

What happens when 20,000+ LLM agents interact autonomously on a social media platform for a full year? We studied Chirper (a Twitter-like world for AIs) and found: gendered language is fluid, not fixed networks still show strong gender homophily both selection and social influence shape AI societies

Preprint: Collaboration improves community-based content moderation, but only when political identities stay implicit. We tested whether you can combine @wikipedia.org model & Community Notes: complicated! w/ Gabriela Juncosa, Saeedeh Mohammadi & @msamahita.bsky.social @wikiresearch.bsky.social

Chapter 3: @helenmargetts.bsky.social & Cosmina Dorobantu on how CSS can improve public policymaking, from better detection and prediction to ethical, accountable use of AI in government. A powerful case for impact beyond academia. doi.org/10.4337/9781... @oii.ox.ac.uk @lsedatascience.bsky.social

1) thank you . 2) the eBook is 42 euros, and the paperback will be out soon with the same price as the paperback. The Handbook is nearly 1000 pages and 42 euros for the paperback is very reasonable, don't you think?

Chapter 2: Duncan Watts & @davidlazer.bsky.social reflect on how the field has evolved from early simulation models to today’s large-scale data and experiments, and ask how can computational social science move from producing insights to having real societal impact? @nunetsi.bsky.social

1) Due to popular demand, the abstract deadline has been extended to 👉Jan 30👈 -- plz share! 2) We are delighted to announce our keynote speaker -- Taha Yasseri @tahayasseri.bsky.social Chair of Technology and Society @ Trinity College Dublin & Technological University Dublin ▶️ cs2italy.org

Tomorrow @wikipedia.org turns 25! Happy birthday to everyone who reads and edits it, and to one of the most important projects in the modern information landscape. Here is the list of the most viewed and most edited articles of "all time". @wikiresearch.bsky.social

Wikipedia is a fascinating case study in collective intelligence, and a rare example of the internet working as intended. @tahayasseri.bsky.social had a great conversation with @bernyoung.bsky.social on @ABC Radio Nightlife this week about Wikipedia as it turns 25. @tcdsociology.bsky.social

ICYMI -- Delighted that the Handbook of Computational Social Science is finally out. Amazing cast of coauthors, with special thanks to @tahayasseri.bsky.social for leading the effort. Happy Holidays! www.elgaronline.com/edcollbook/b...

Excited to see this out! congrats to @tahayasseri.bsky.social & all contributors!

Part I: "Foundations" | |>Chapter 6: "Computational inductive research" In which I argue for the foundational place of inductive research in computational social science, rooted in interpretation, transparency, and validation. Thanks @tahayasseri.bsky.social for shepherding this handbook through

Thrilled to announce the Handbook of Computational Social Science is officially out! 956 pages, 118 authors, and truly global, interdisciplinary perspectives. Deep thanks to the contributors and anonymous reviewers who shaped this over 4 years. Buy your copy now! @elgarpublishing.bsky.social

We have an opening for a PhD position at SOHAM to work on a very cool project (COOLNET)! Supervised by Guillaume Falmagne, Ph.D. and Prof @tahayasseri.bsky.social, they will work on large-scale multiplayer video games to study and compare mechanisms that foster global cooperation in social dilemmas.

The next ECSR conference is brought to you by @tcdsociology.bsky.social and @esri.ie! Trinity College Dublin, 15-16 June 2026 www.ecsr2026.net #ECSR2026 Abstract submission deadline: 11 January 2026

A few updates on our Grokipedia analysis: we expanded our sample to 20,000 most edited articles on Wikipedia. Linguistic & stylistic differences are the same as reported before (Generally, Grokipedia articles are longer, more difficult to read, and less referenced.) @wikiresearch.bsky.social

🚨New Research 🚨 Humans bring gender biases to our interactions with AI. In iScience from our Prof @tahayasseri.bsky.social , visiting postdoc Sepideh Bazazi and Jurgis Karpus. 🤖Read more: tinyurl.com/wd3c67d9 @tcdschoolssp.bsky.social

We're hiring 2 Assistant Professors of Sociology: Gender and Sexuality and Environmental Sociology. At @tcdsociology.bsky.social, we aspire to be a method-agnostic group of solution-oriented sociologists. Join our welcoming community at @tcdschoolssp.bsky.social. Deadline 1 Dec. Link in the comment.

#Grokipedia set out to “fix” #Wikipedia. Turns out it mostly rewrites it, longer, slicker, less sourced. Fluent, but fragile. @wikiresearch.bsky.social