Computational Social Science Working Group
The CSS Working Group uses computational and mathematical approaches to investigate social behavior. We are interested in the empirical analysis of social phenomenon. Recent projects include:
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Visual communication dynamics on Facebook, Instagram, and TikTok.
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Game-theoretic modeling of bias arising from large-language models (LLMs).
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Network-based interventions of tax evasion in offshore financial centers.
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Surveys of political attitudes and misinformation belief.
We also work on the development of methodological tools, such as deep learning for image analysis, social network analysis, ChatGPT & LLM workstreams, simulation, and integrating journalistic and creative approaches. If you are an undergraduate interested in research, please reach out and let's chat!
The group is growing and I'm accepting applications for a post-doc in the 2024 cycle. If you are interested in social media, modeling/machine learning, or AI & game theory, please get in touch at herbert@dartmouth.edu with your C.V.
Faculty Investigator
Herbert Chang
I'm excited to work with students to develop their core social science areas through student-led projects, whether it's in politics, public policy, AI, or sociology. We can always find the right data and computational tools for each project, so long as they bring interest and motivation. I am also committed to helping students succeed later in their careers, whether it is for further study or transition to industry.
Undergraduate Researchers
Sunny Fang
Yu (Sunny) Fang is a data science and political science student at Barnard College, Columbia University. Her research employs computational methods to study democratic values, such as media portrayal of geopolitics and online discourse about Taiwan. Previously, she has written about the legal and global implications of Taiwan's semiconductor dominance in the Columbia Undergraduate Law Review and the Asia-Pacific Affairs Council Journal of Columbia.
Key themes: Social media and politics
Sean Noh '28
I'm from Virginia and will be attending Dartmouth next year to study Computer Science, and I'm also interested in education, QSS, and psychology. I hope to develop educational technology and learn application development. I love playing tabletop games, I am an Eagle Scout, and I recently published a habit-tracking app, Cogo.
Key themes: AI and game theory
Tracy Weener '26
Tracy Weener is a public policy science research intern, saxophonist in the Wind Ensemble, associate editor of the Law Journal, and Women in Business associate. After graduating, Tracy intends to apply data science to government through work in policy analysis. Her paper "Conjoint Analysis of the 2024 Taiwanese Presidential Election" won the NATSA Undergraduate Paper Competition. She is from Boxford, Massachusetts.
Key themes: Survey experiments, Taiwanese politics, misinformation, youth politics
Zachariah Yusaf '26
Zachariah Yusaf is a sophomore at Dartmouth College, where he plans to major in mathematics and minor in philosophy. Zach is particularly interested in how artificial intelligence and discourse can shape geopolitical outcomes. At Dartmouth, Zach dances on Raaz, debates for the Parliamentary Debate team, writes for The Dartmouth, and was a Rockefeller Center First Year Fellow.
Key themes: Social network analysis
Mingyue Zha '27
Mingyue Zha is a freshman at Dartmouth College studying Economics and Neuroscience. After moving from Shanghai, China to Connecticut, she did fMRI research at the Yale School of Medicine’s Department of Psychiatry. She’s interested in doing research on attention economics, social networks, and online streaming communities.
Key themes: attention economics, platforms and social networks
Alumni Hall of Fame
Joanna Olagundoye '28
Analyst at Baringa Partners
V Quidore '24
Assistant Librarian
Sam Winchester '24
Investor at Radian Capital
Datasets and Research Streams
These are existing streams of research, based on existing databases. We have capabilities to scrape TikTok, Instagram, and YouTube. Students' own interests, questions, and data sources are encouraged. For internal tools, please consult our Slack channel.
COVID-19 Twitter Dataset
The largest public Twitter dataset for COVID-19 (n > 4 billion). Can be used to analyze discourse and specific topics of interest. Past examples include politics, K-pop, and public health.
Instagram & the Floyd Protests
Dataset of more than 1.59 million public Instagram posts during the #BLM2020 protests following the murder of Mr. George Floyd. This stream combines social justice and visual machine learning. *Seeking RAs.
News & Media
For students interested in journalism, media framing, and partisan bias, there are rich opportunities to cultivate your own area of research. Combines NLP, LLM and ChatGPT workstreams, and partisan bias. Examples include Gender in the 2020 Democratic Primaries and Debiasing AI from LGBTQ+ Bias.
Vaping
Multimodal dataset across YouTube, Instagram, TikTok, and Twitch of tobacco and alcohol abuse. Entry points in deep learning, social network analysis, and surveys.