Meiqing Zhang's research interests lie in computational social science and political communication. She teaches courses on natural language processing and data science.
Her research applies natural language processing and machine learning to the study of political polarization, political advertising and evolution of political values. She has spent time conducting research at Meta Core Data Science, Wesleyan Media Project, and NORC at the University of Chicago. She welcomes students from both computer science and the social sciences to work with her.
Selected Publications:
Zhang, M., Cakmak, F., Neumann, M., ... & Fowler, E. F. (2025). Comparable 2022 General Election Advertising Datasets from Meta and Google. Scientific Data, 12(1), 968.
González-Bailón, S., Lazer, D., Barberá, P., Zhang, M., ... & Tucker, J. A. (2023). Asymmetric ideological segregation in exposure to political news on Facebook. Science, 381(6656), 392-398.
2025-2026 Courses:
Natural Language Processing (COMP 331)
Special Topics in Social Data Science (COMP 395)
Fundamentals of Computer Science (COMP 131)