Alvin Zhou

Alvin Zhou is an Assistant Professor at the Hubbard School of Journalism and Mass Communication. His research centers on three areas: generative AI, computational social science, and strategic communication. His earlier work examined the intersection of the latter two, and his current work focuses on generative AI and its differential effects across levels of communicative entities.

His research treats generative AI as a technology that enters an existing ecology of messages, organizations, and publics and rearranges the advantages already distributed there, privileging certain messages, benefiting certain organizations, and reshaping what individuals encounter. He studies these dynamics with computational methods and causal inference, extending an earlier agenda on information, communication, and organizations, and also uses AI itself as a method alongside these tools. Much of this rearrangement plays out in strategic communication, where campaigns, brands, advocacy groups, and government communicators distribute their messages through the same systems that decide which messages circulate; his work asks where those advantages come from and what they mean for prosocial outcomes. This same sociological perspective on communication runs through his earlier work on stakeholder engagement and public relationships as pathways through which organizations change their network ecologies. With an interdisciplinary research background, he is a core member of the UMN AI Hub and holds affiliated roles across the College of Liberal Arts (CLA), including the Center for the Study of Political Psychology, the Minnesota Journalism Center, the School of Statistics, Asian American Studies, and the Minnesota Computational Advertising Lab (MCAL).

His work has appeared in general communication journals (e.g., New Media & Society, Journal of Communication, Journal of Computer-Mediated Communication, and Mass Communication and Society), field-top journals (e.g., Journal of Public Relations Research, Journal of Advertising, Political Communication, and Management Communication Quarterly), and computer science conference proceedings (e.g., CSCW). His research has received major recognitions from the International Communication Association (ICA), the National Communication Association (NCA), the Association for Education in Journalism and Mass Communication (AEJMC), and the Public Relations Society of America (PRSA), including the 2019 and 2025 ICA Robert Heath Awards, the 2020 NCA PRIDE Article of the Year Award, and the 2024 IPRRC Fullintel Media Insights and Impact Award. He serves on the editorial boards of the Journal of Communication and six top strategic communication journals, and has edited two special issues, one on Generative AI for Computational Communication Research and one on computational strategic communication for Public Relations Review.

Dr. Zhou earned his Ph.D. in Communication from the University of Pennsylvania's Annenberg School. He also holds an M.A. in Statistics and Data Science from the Wharton School and an M.A. in Strategic Public Relations from the University of Southern California's Annenberg School. He earned dual bachelor's degrees in Mechanical Engineering and Journalism from Tsinghua University. At Hubbard, he teaches courses on computational social science and digital media and mentors students in applying data-analytic insights to journalistic and strategic communication work.