Bio

Jennifer Pan is a political scientist whose research focuses on political communication, digital media, and authoritarian politics. She is the Sir Robert Ho Tung Professor of Chinese Studies, Professor of Communication and (by courtesy) Political Science, and a Senior Fellow at the Freeman Spogli Institute.

Dr. Pan's research uses experimental and computational methods with large-scale datasets on political activity to answer questions about the role of digital media in authoritarian and democratic politics, including how political censorship, propaganda, and information manipulation work in the digital age and how preferences and behaviors are shaped as a result. Her work has appeared in peer-reviewed publications such as the American Political Science Review, American Journal of Political Science, Journal of Politics, Political Communication, 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)

Contact

  • Academic
    jp1@stanford.edu
    University - Faculty Department: Communication Position: Professor
    • 450 Jane Stanford Way Bldg 120 Rm 110
    • Stanford,  California  94305-2030 
    University - Faculty Department: Stanford Center on China's Economy and Institutions (SCCEI) Position: Senior Fellow

Additional Info

Links

2024-25 Courses

Stanford Advisees

All Publications

  • Gender and Political Compliance Under Authoritarian Rule COMPARATIVE POLITICAL STUDIES Fan, Y., Pan, J., Zhang, T. 2024

    View details for DOI 10.1177/00104140241283007

    View details for Web of Science ID 001317015600001

  • January 6 arrests and media coverage do not remobilize conservatives on social media. Proceedings of the National Academy of Sciences of the United States of America Dahlke, R., Pan, J. 2024; 121 (23): e2401239121

    Abstract

    Social media's pivotal role in catalyzing social movements is widely acknowledged across scientific disciplines. Past research has predominantly explored social media's ability to instigate initial mobilization while leaving the question of its capacity to sustain these movements relatively uncharted. This study investigates the persistence of movement activity on Twitter and Gab following a substantial on-the-ground mobilization event catalyzed by social media-the StoptheSteal movement culminating in the January 6th Capitol attack. Our findings indicate that the online communities active in the January 6 mobilization did not display substantial remobilization in the subsequent year. These results highlight the fact that further exploration is needed to understand the factors shaping how and when movements are sustained by social media. In this regard, our study provides valuable insights for scientists across diverse disciplines, on how certain social media platforms may contribute to the evolving dynamics of collective action.

    View details for DOI 10.1073/pnas.2401239121

    View details for PubMedID 38805294

  • The effects of Facebook and Instagram on the 2020 election: A deactivation experiment. Proceedings of the National Academy of Sciences of the United States of America Allcott, H., Gentzkow, M., Mason, W., Wilkins, A., Barberá, P., Brown, T., Cisneros, J. C., Crespo-Tenorio, A., Dimmery, D., Freelon, D., González-Bailón, S., Guess, A. M., Kim, Y. M., Lazer, D., Malhotra, N., Moehler, D., Nair-Desai, S., Nait El Barj, H., Nyhan, B., Paixao de Queiroz, A. C., Pan, J., Settle, J., Thorson, E., Tromble, R., Velasco Rivera, C., Wittenbrink, B., Wojcieszak, M., Zahedian, S., Franco, A., Kiewiet de Jonge, C., Stroud, N. J., Tucker, J. A. 2024; 121 (21): e2321584121

    Abstract

    We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

    View details for DOI 10.1073/pnas.2321584121

    View details for PubMedID 38739793

  • Reporting after removal: the effects of journalist expulsion on foreign news coverage JOURNAL OF COMMUNICATION Debutts, M., Pan, J. 2024

    View details for DOI 10.1093/joc/jqae015

    View details for Web of Science ID 001214419700001

  • Partisan conflict over content moderation is more than disagreement about facts. Science advances Appel, R. E., Pan, J., Roberts, M. E. 2023; 9 (44): eadg6799

    Abstract

    Social media companies have come under increasing pressure to remove misinformation from their platforms, but partisan disagreements over what should be removed have stymied efforts to deal with misinformation in the United States. Current explanations for these disagreements center on the "fact gap"-differences in perceptions about what is misinformation. We argue that partisan differences could also be due to "party promotion"-a desire to leave misinformation online that promotes one's own party-or a "preference gap"-differences in internalized preferences about whether misinformation should be removed. Through an experiment where respondents are shown false headlines aligned with their own or the opposing party, we find some evidence of party promotion among Democrats and strong evidence of a preference gap between Democrats and Republicans. Even when Republicans agree that content is false, they are half as likely as Democrats to say that the content should be removed and more than twice as likely to consider removal as censorship.

    View details for DOI 10.1126/sciadv.adg6799

    View details for PubMedID 37922349

    View details for PubMedCentralID PMC10624338

  • Author Correction: Like-minded sources on Facebook are prevalent but not polarizing. Nature Nyhan, B., Settle, J., Thorson, E., Wojcieszak, M., Barberá, P., Chen, A. Y., Allcott, H., Brown, T., Crespo-Tenorio, A., Dimmery, D., Freelon, D., Gentzkow, M., González-Bailón, S., Guess, A. M., Kennedy, E., Kim, Y. M., Lazer, D., Malhotra, N., Moehler, D., Pan, J., Thomas, D. R., Tromble, R., Rivera, C. V., Wilkins, A., Xiong, B., de Jonge, C. K., Franco, A., Mason, W., Stroud, N. J., Tucker, J. A. 2023

    View details for DOI 10.1038/s41586-023-06795-x

    View details for PubMedID 37914941

  • Reshares on social media amplify political news but do not detectably affect beliefs or opinions. Science (New York, N.Y.) Guess, A. M., Malhotra, N., Pan, J., Barberá, P., Allcott, H., Brown, T., Crespo-Tenorio, A., Dimmery, D., Freelon, D., Gentzkow, M., González-Bailón, S., Kennedy, E., Kim, Y. M., Lazer, D., Moehler, D., Nyhan, B., Rivera, C. V., Settle, J., Thomas, D. R., Thorson, E., Tromble, R., Wilkins, A., Wojcieszak, M., Xiong, B., de Jonge, C. K., Franco, A., Mason, W., Stroud, N. J., Tucker, J. A. 2023; 381 (6656): 404-408

    Abstract

    We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, US-based users to feeds that did not contain any reshares over a 3-month period. We find that removing reshared content substantially decreases the amount of political news, including content from untrustworthy sources, to which users are exposed; decreases overall clicks and reactions; and reduces partisan news clicks. Further, we observe that removing reshared content produces clear decreases in news knowledge within the sample, although there is some uncertainty about how this would generalize to all users. Contrary to expectations, the treatment does not significantly affect political polarization or any measure of individual-level political attitudes.

    View details for DOI 10.1126/science.add8424

    View details for PubMedID 37499012

  • Asymmetric ideological segregation in exposure to political news on Facebook. Science (New York, N.Y.) González-Bailón, S., Lazer, D., Barberá, P., Zhang, M., Allcott, H., Brown, T., Crespo-Tenorio, A., Freelon, D., Gentzkow, M., Guess, A. M., Iyengar, S., Kim, Y. M., Malhotra, N., Moehler, D., Nyhan, B., Pan, J., Rivera, C. V., Settle, J., Thorson, E., Tromble, R., Wilkins, A., Wojcieszak, M., de Jonge, C. K., Franco, A., Mason, W., Stroud, N. J., Tucker, J. A. 2023; 381 (6656): 392-398

    Abstract

    Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election using aggregated data for 208 million US Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged. We show that (i) ideological segregation is high and increases as we shift from potential exposure to actual exposure to engagement; (ii) there is an asymmetry between conservative and liberal audiences, with a substantial corner of the news ecosystem consumed exclusively by conservatives; and (iii) most misinformation, as identified by Meta's Third-Party Fact-Checking Program, exists within this homogeneously conservative corner, which has no equivalent on the liberal side. Sources favored by conservative audiences were more prevalent on Facebook's news ecosystem than those favored by liberals.

    View details for DOI 10.1126/science.ade7138

    View details for PubMedID 37499003

  • How do social media feed algorithms affect attitudes and behavior in an election campaign? Science (New York, N.Y.) Guess, A. M., Malhotra, N., Pan, J., Barberá, P., Allcott, H., Brown, T., Crespo-Tenorio, A., Dimmery, D., Freelon, D., Gentzkow, M., González-Bailón, S., Kennedy, E., Kim, Y. M., Lazer, D., Moehler, D., Nyhan, B., Rivera, C. V., Settle, J., Thomas, D. R., Thorson, E., Tromble, R., Wilkins, A., Wojcieszak, M., Xiong, B., de Jonge, C. K., Franco, A., Mason, W., Stroud, N. J., Tucker, J. A. 2023; 381 (6656): 398-404

    Abstract

    We investigated the effects of Facebook's and Instagram's feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users' on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.

    View details for DOI 10.1126/science.abp9364

    View details for PubMedID 37498999

  • Like-minded sources on Facebook are prevalent but not polarizing. Nature Nyhan, B., Settle, J., Thorson, E., Wojcieszak, M., Barberá, P., Chen, A. Y., Allcott, H., Brown, T., Crespo-Tenorio, A., Dimmery, D., Freelon, D., Gentzkow, M., González-Bailón, S., Guess, A. M., Kennedy, E., Kim, Y. M., Lazer, D., Malhotra, N., Moehler, D., Pan, J., Thomas, D. R., Tromble, R., Rivera, C. V., Wilkins, A., Xiong, B., de Jonge, C. K., Franco, A., Mason, W., Stroud, N. J., Tucker, J. A. 2023

    Abstract

    Many critics raise concerns about the prevalence of 'echo chambers' on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from 'like-minded' sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

    View details for DOI 10.1038/s41586-023-06297-w

    View details for PubMedID 37500978

    View details for PubMedCentralID 9524832

  • Strategies of Chinese State Media on Twitter POLITICAL COMMUNICATION Fan, Y., Pan, J., Sheng, J. 2023

    View details for DOI 10.1080/10584609.2023.2233911

    View details for Web of Science ID 001025046100001

  • How Information Flows from the World to China INTERNATIONAL JOURNAL OF PRESS-POLITICS Lu, Y., Schaefer, J., Park, K., Joo, J., Pan, J. 2022

    View details for DOI 10.1177/19401612221117470

    View details for Web of Science ID 000837345900001

  • How government-controlled media shifts policy attitudes through framing POLITICAL SCIENCE RESEARCH AND METHODS Pan, J., Shao, Z., Xu, Y. 2022; 10 (2): 317-332

    View details for DOI 10.1017/psrm.2021.35

    View details for Web of Science ID 000777984100008

  • The digital repression of social movements, protest, and activism: A synthetic review. Science advances Earl, J., Maher, T. V., Pan, J. 2022; 8 (10): eabl8198

    Abstract

    Repression research examines the causes and consequences of actions or policies that are meant to, or actually do, raise the costs of activism, protest, and/or social movement activity. The rise of digital and social media has brought substantial increases in attention to the repression of digital activists and movements and/or to the use of digital tools in repression, which is spread across many disciplines and areas of study. We organize and review this growing welter of research under the concept of digital repression by expanding a typology that distinguishes actions based on actor type, whether actions are overt or covert, and whether behaviors are shaped by coercion or channeling. This delineation between broadly different forms of digital repression allows researchers to develop expectations about digital repression, better understand what is "new" about digital repression in terms of explanatory factors, and better understand the consequences of digital repression.

    View details for DOI 10.1126/sciadv.abl8198

    View details for PubMedID 35263143

  • Selectively localized: Temporal and visual structure of smartphone screen activity across media environments MOBILE MEDIA & COMMUNICATION Muise, D., Lu, Y., Pan, J., Reeves, B. 2022

    View details for DOI 10.1177/20501579221080333

    View details for Web of Science ID 000761615000001

  • Does ideology influence hiring in China? evidence from two randomized experiments POLITICAL SCIENCE RESEARCH AND METHODS Pan, J., Zhang, T. 2022

    View details for DOI 10.1017/psrm.2021.77

    View details for Web of Science ID 000750662100001

  • Response to Manfred Elstrom's Review of Welfare for Autocrats: How Social Assistance in China Cares for its Rulers PERSPECTIVES ON POLITICS Pan, J. 2021; 19 (4)

    View details for DOI 10.1017/S1537592721003212

    View details for Web of Science ID 000728285000025

  • Workers and Change in China: Resistance, Repression, Responsiveness (Book Review) PERSPECTIVES ON POLITICS Book Review Authored by: Pan, J. 2021; 19 (4): 1274-1276

    View details for DOI 10.1017/S1537592721002851

    View details for Web of Science ID 000728285000022

  • Response to Manfred Elstrom's Review of Welfare for Autocrats: How Social Assistance in China Cares for its Rulers PERSPECTIVES ON POLITICS Pan, J. 2021; 19 (4): 1278-1279

    View details for Web of Science ID 000728285000108

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

    View details for DOI 10.1080/10584609.2020.1765914

    View details for Web of Science ID 000550071300001

  • How Saudi Crackdowns Fail to Silence Online Dissent AMERICAN POLITICAL SCIENCE REVIEW Pan, J., Siegel, A. A. 2020; 114 (1): 109–25

    View details for DOI 10.1017/S0003055419000650

    View details for Web of Science ID 000504568700008

  • Censorship's Effect on Incidental Exposure to Information: Evidence From Wikipedia SAGE OPEN Pan, J., Roberts, M. E. 2020; 10 (1)

    View details for DOI 10.1177/2158244019894068

    View details for Web of Science ID 000517294700001

  • Online field experiments ASIAN JOURNAL OF COMMUNICATION Muise, D., Pan, J. 2019; 29 (3): 217–34

    View details for DOI 10.1080/01292986.2018.1453850

    View details for Web of Science ID 000467880200002

  • How Chinese Officials Use the Internet to Construct Their Public Image POLITICAL SCIENCE RESEARCH AND METHODS Pan, J. 2019; 7 (2): 197–213

    View details for DOI 10.1017/psrm.2017.15

    View details for Web of Science ID 000466762400001

  • Screenomics: a framework to capture and analyze personal life experiences and the ways that technology shapes them Human-Computer Interaction Reeves, B. 2019

    View details for DOI 10.1080/07370024.2019.1578652

  • How the Market for Social Media Shapes Strategies of Internet Censorship DIGITAL MEDIA AND DEMOCRATIC FUTURES Pan, J., DelliCarpini, M. X. 2019: 196–230

    View details for Web of Science ID 000464289800009

  • 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

    View details for Web of Science ID 000488766000004

  • 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

    View details for DOI 10.1177/0081175019860244

    View details for Web of Science ID 000501594000005

  • 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

    View details for DOI 10.1177/0081175019866425

    View details for Web of Science ID 000501594000009

  • Concealing Corruption: How Chinese Officials Distort Upward Reporting of Online Grievances AMERICAN POLITICAL SCIENCE REVIEW Pan, J., Chen, K. 2018; 112 (3): 602–20

    View details for DOI 10.1017/S0003055418000205

    View details for Web of Science ID 000437428100011

  • China's Newsmakers: Official Media Coverage and Political Shifts in the Xi Jinping Era CHINA QUARTERLY Jaros, K., Pan, J. 2018; 233: 111–36

    View details for DOI 10.1017/S0305741017001679

    View details for Web of Science ID 000428650500006

  • 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

  • Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies Field, A., Kliger, D., Wintner, S., Pan, J., Jurafsky, D., Tsvetkov, Y., Assoc Computat Linguist ASSOC COMPUTATIONAL LINGUISTICS-ACL. 2018: 3570-3580

    View details for Web of Science ID 000865723403082

  • 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

    View details for DOI 10.1017/S0003055417000144

    View details for Web of Science ID 000406688200004

  • 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

    View details for DOI 10.1177/0010414014556212

    View details for Web of Science ID 000394902400001

  • 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

    View details for DOI 10.1080/10758216.2016.1181525

    View details for Web of Science ID 000402099100005

  • 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

    View details for DOI 10.1017/S1049096514001760

    View details for Web of Science ID 000347159500026

  • Reverse-engineering censorship in China: Randomized experimentation and participant observation SCIENCE King, G., Pan, J., Roberts, M. E. 2014; 345 (6199): 891-891

    View details for DOI 10.1126/science.1251722

    View details for Web of Science ID 000340524700035

  • 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

    View details for DOI 10.1017/S0003055413000014

    View details for Web of Science ID 000318942500007

https://orcid.org/0000-0002-4818-0122