Bio


Jennifer Pan is an Associate Professor of Communication at Stanford University. Her research focuses on political communication and authoritarian politics. Pan uses experimental and computational methods with large-scale datasets on political activity in China and other authoritarian regimes to answer questions about how autocrats perpetuate their rule. How political censorship, propaganda, and information manipulation work in the digital age. How preferences and behaviors are shaped as a result.

Her book, Welfare for Autocrats: How Social Assistance in China Cares for its Rulers (Oxford, 2020) shows how China's pursuit of political order transformed the country’s main social assistance program, Dibao, for repressive purposes. Her work has appeared in peer reviewed publications such as the American Political Science Review, American Journal of Political Science, Comparative Political Studies, Journal of Politics, and Science.

She graduated from Princeton University, summa cum laude, and received her Ph.D. from Harvard University’s Department of Government.

Academic Appointments


Program Affiliations


  • Center for East Asian Studies

Professional Education


  • BA, Princeton University, School of Public and International Affairs (2004)
  • PhD, Harvard University, Government (2015)

2021-22 Courses


Stanford Advisees


All Publications


  • Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them. Human-computer interaction Reeves, B. n., Ram, N. n., Robinson, T. N., Cummings, J. J., Giles, C. L., Pan, J. n., Chiatti, A. n., Cho, M. J., Roehrick, K. n., Yang, X. n., Gagneja, A. n., Brinberg, M. n., Muise, D. n., Lu, Y. n., Luo, M. n., Fitzgerald, A. n., Yeykelis, L. n. 2021; 36 (2): 150–201

    Abstract

    Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave - often within seconds - among multiple applications, locations, functions and media. We describe an end-to-end system for capturing and analyzing the "screenome" of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple time scale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory and privacy.

    View details for DOI 10.1080/07370024.2019.1578652

    View details for PubMedID 33867652

    View details for PubMedCentralID PMC8045984

  • Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visibility POLITICAL COMMUNICATION Lu, Y., Pan, J. 2020
  • How Saudi Crackdowns Fail to Silence Online Dissent AMERICAN POLITICAL SCIENCE REVIEW Pan, J., Siegel, A. A. 2020; 114 (1): 109–25
  • Censorship's Effect on Incidental Exposure to Information: Evidence From Wikipedia SAGE OPEN Pan, J., Roberts, M. E. 2020; 10 (1)
  • Online field experiments ASIAN JOURNAL OF COMMUNICATION Muise, D., Pan, J. 2019; 29 (3): 217–34
  • How Chinese Officials Use the Internet to Construct Their Public Image POLITICAL SCIENCE RESEARCH AND METHODS Pan, J. 2019; 7 (2): 197–213
  • REJOINDER: THE CHALLENGES OF "MORE DATA" FOR PROTEST EVENT ANALYSIS SOCIOLOGICAL METHODOLOGY, VOL 49 Zhang, H., Pan, J., Alwin, D. F. 2019; 49: 76–82
  • Screenomics: a framework to capture and analyze personal life experiences and the ways that technology shapes them Human-Computer Interaction Reeves, B. 2019
  • How the Market for Social Media Shapes Strategies of Internet Censorship DIGITAL MEDIA AND DEMOCRATIC FUTURES Pan, J., DelliCarpini, M. X. 2019: 196–230
  • Computational Communication Science: A Methodological Catalyzer for a Maturing Discipline INTERNATIONAL JOURNAL OF COMMUNICATION Hilbert, M., Barnett, G., Blumenstock, J., Contractor, N., Diesner, J., Frey, S., Gonzalez-Bailon, S., Lamberso, P. J., Pan, J., Tai-Quan Peng, Shen, C., Smaldino, P. E., Van Atteveldt, W., Waldherr, A., Zhang, J., Zhu, J. H. 2019; 13: 3912–34
  • CASM: A DEEP-LEARNING APPROACH FOR IDENTIFYING COLLECTIVE ACTION EVENTS WITH TEXT AND IMAGE DATA FROM SOCIAL MEDIA SOCIOLOGICAL METHODOLOGY, VOL 49 Zhang, H., Pan, J., Alwin, D. F. 2019; 49: 1–57
  • Concealing Corruption: How Chinese Officials Distort Upward Reporting of Online Grievances AMERICAN POLITICAL SCIENCE REVIEW Pan, J., Chen, K. 2018; 112 (3): 602–20
  • China's Newsmakers: Official Media Coverage and Political Shifts in the Xi Jinping Era CHINA QUARTERLY Jaros, K., Pan, J. 2018; 233: 111–36
  • China's Ideological Spectrum JOURNAL OF POLITICS Pan, J., Xu, Y. 2018; 80 (1): 254–73

    View details for DOI 10.1086/694255

    View details for Web of Science ID 000419487800033

  • How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument AMERICAN POLITICAL SCIENCE REVIEW King, G., Pan, J., Roberts, M. E. 2017; 111 (3): 484–501
  • Conditional Receptivity to Citizen Participation: Evidence From a Survey Experiment in China COMPARATIVE POLITICAL STUDIES Meng, T., Pan, J., Yang, P. 2017; 50 (4): 399-433
  • How Market Dynamics of Domestic and Foreign Social Media Firms Shape Strategies of Internet Censorship PROBLEMS OF POST-COMMUNISM Pan, J. 2017; 64 (3-4): 167–88
  • Sources of Authoritarian Responsiveness: A Field Experiment in China AMERICAN JOURNAL OF POLITICAL SCIENCE Chen, J., Pan, J., Xu, Y. 2016; 60 (2): 383-400

    View details for DOI 10.1111/ajps.12207

    View details for Web of Science ID 000374005500007

  • No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science PS-POLITICAL SCIENCE & POLITICS Monroe, B. L., Pan, J., Roberts, M. E., Sen, M., Sinclair, B. 2015; 48 (1): 71-74
  • Reverse-engineering censorship in China: Randomized experimentation and participant observation SCIENCE King, G., Pan, J., Roberts, M. E. 2014; 345 (6199): 891-891
  • How Censorship in China Allows Government Criticism but Silences Collective Expression AMERICAN POLITICAL SCIENCE REVIEW King, G., Pan, J., Roberts, M. E. 2013; 107 (2): 326-343