Research

Professor Budak’s research interests lie in the area of computational social science– and particularly in the use of large scale data sets and computational techniques to study problems with policy, social and political implications. 

Selected Publications

Please also see Ceren Budak’s Curriculum Vitae (CV).

Bode, L., C. Budak, et al, Words that Matter: How the News and Social Media Shaped the 2016 Presidential Campaign. 2020, Brookings Institution Press.

Budak, C., D. Agrawal and A. El Abbadi, Limiting the spread of misinformation in social networks, Proceedings of the 20th international conference on World wide web, 665-674, 2011.

Budak, C., S. Goel and J.M. Rao, Fair and balanced? Quantifying media bias through crowdsourced content analysis, Public Opinion Quarterly, 2-16. 80 (S1), 250-271

Singh, L. et al, A first look at COVID-19 information and misinformation sharing on Twitter, 2020.

Research Projects

Measuring and Promoting the Quality of Online News Discussions. Funded by the National Science Foundation, the project is a joint effort between researchers at the University of Michigan School of Information (Paul Resnick) and the Ohio State University School of Communication (R. Kelly Garrett).

Network-transforming Interventions for Reducing the Spread of Health Misinformation Online. Funded by the Social Science Research Council, this grant (2022-2024) will develop network altering interventions on social media to limit the spread of health misinformation.

CAREER: Large-Scale Examination of Problematic Online Behaviors and their Regulators. Funded by the National Science Foundation, this project will identify (i.) which regulators (market, architecture or norms), or strategies, are suitable or most effective for combating disinformation and cross-partisan animosity online; (ii.) how their strengths vary across behaviors and social media platforms; and (iii.) how these regulators interact, at times undermining or supporting each other.

GCR: The Future of Quantitative Research in Social Science. This collaborative project funded by the National Science Foundation aims to develop methods, case examples, and basic infrastructure to help social science researchers to use social media data to answer traditional social science research questions. 

CHS: Small: Systematic Comparative and Historical Analysis Framework for Contentious Politics. This project develops data collection and labeling techniques to use social
media to study online social movements.

CHS Small: Collaborative Research: Measuring and Promoting the Quality of Online News Discussions. This project aims to develop techniques to measure and improve the quality of discussions in online news spaces.