Stanford Prof. | political communication | digital media | China | authoritarian politics | computational social science
Stanford, CA
Joined June 2010
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Jennifer Pan retweeted
New paper with @jenjpan and @xuyiqing in @BJPolS! “Selection, Stability, and Shock: Political Attitudes of Chinese Students at Home and Abroad” Does studying in the US make Chinese students more liberal, or does it trigger a nationalist backlash? doi.org/10.1017/S00071234261…
Jennifer Pan retweeted
Read our chapter here! preprints.apsanet.org/engage…
The key claim: "AI is more likely to reinforce existing patterns of [information] exposure and behavior than it is to transform how people understand and relate to the political world"
(with @jenjpan, @aasiegel, and @YamilRVelez)
Political Scientists on AI
This is an interesting collection of essays prepared by @persily and @j_a_tucker that discusses how AI is reshaping politics & how political scientists study politics. A timely contribution to a key discussion.
Open Access: apsanet.org/wp-content/uploa…
New study out in Nature Human Behaviour: 37 million US users were exposed to deceptive networks on Facebook & 3 million on Instagram during the 2020 elections—roughly 15% and 2% of active users. 🧵
Deceptive networks disproportionately reached users who were older, more conservative, more frequently exposed to untrustworthy sources, and spent more time on Facebook.
This was a huge team effort with an amazing group of co-authors @rutheappel @ymkim5wi @xuyiqing @danrthomas @winteram @j_a_tucker @TaliaStroud
and many more. Grateful to everyone involved. Full paper: rdcu.be/fbU8b
New paper with @xuxupolitics in @PNASNexus: China origin LLMs refuse political questions at dramatically higher rates than US models — BaiChuan refused 60% of prompts, DeepSeek 36%. This holds in Chinese and English, ow.ly/vmfp50Yl8KC
Chinese chatbots are likely censored by the Chinese government, and will often refuse to answer or provide inaccurate answers to politically charged questions, regardless of whether they are posed in English or Chinese. In PNAS Nexus: ow.ly/vmfp50Yl8KC
ALT Refusal to respond with mean and 95% confidence intervals.
Jennifer Pan retweeted
China’s chatbots are censored by the state. In our @PNASNexus paper with @jenjpan, we find substantially higher levels of political censorship in large language models (LLMs) originating from China than those developed outside China. doi.org/10.1093/pnasnexus/pg…🧵
Jennifer Pan retweeted
Why do authoritarian states charge political opponents with non-political crimes? In our @The_JOP paper with @jenjpan & @xuyiqing, we examine how *Disguised Repression* undermines opponents’ moral authority and mobilization capacity. doi.org/10.1086/734267🧵
Jennifer Pan retweeted
Excited to share our new publication in @PNASNews! Through four analyses on 435,261 Weibo posts and 8.26 million news articles, we found that Chinese state media wasn't the main gatekeeper of information about Russia’s invasion of Ukraine for Weibo users: pnas.org/doi/10.1073/pnas.24…
Some great news to end the year!! New paper with @YingdanL_kk and @jenjpan! In it, we estimate the influence of foreign (American, Russian, and Ukrainian) and domestic Chinese media on conversations on Weibo about the Russo-Ukrainian War. pnas.org/doi/10.1073/pnas.24…
Jennifer Pan retweeted
Happy to see “Gender and Political Compliance under Authoritarian Rule” (w/ @jenjpan, @yingjie_fan) out @cps_journal! When autocrats do not impose explicit rules of behavior, what does political compliance look like?
journals.sagepub.com/doi/10.…
Jennifer Pan retweeted
(1) The Chinese internet has been vibrant for 30 years, but will it remain that way? In new issue of @CommPublicSAGE, @jenjpan and I explore “disengagement”: that surveillance, censorship, and disenchantment might lead Chinese citizens to disappear from the web (link at end).1/6
Jennifer Pan retweeted
✨ new from me & @jenjpan in @PNASNews. We find that "January 6 arrests and media coverage do not remobilize conservatives on social media," suggesting we need more work to understand under what circumstances social media can _sustain_ movements pnas.org/doi/10.1073/pnas.24…
ALT January 6 arrests and media coverage do not remobilize conservatives on social media
ALT Figure 1 Number of collected (A) tweets made by elite political influencers and (B) Gab posts made by elite political influencers and January-6-related nonelites about January 6 per day in our dataset, January 6, 2021, to April 30, 2022.
ALT Figure 2. Number of (A) media stories about January 6 and (B) arrests of January 6 defendants per day. Black dots represent dates that are two SD or more above the mean number per day.
ALT Figure 3. Histogram of the null distribution of nonparametric testing of change in volume of posts with a 30-d window before and after the focal point. The x-axis represents the change in the number of posts. The y-axis represents the number of days that demonstrated that change. The purple dashed lines represent the 95% CI. The solid, small green lines represent the change in the volume of posts for a given focal point and are sometimes overlapping. Each panel represents a platform (e.g., Twitter or Gab) and a group (e.g., White Nationalists) combination.
Jennifer Pan retweeted
The largest social media deactivation RCT was just published in PNAS: pnas.org/doi/10.1073/pnas.23…
New pub w/ @debutts in @Journal_Of_Comm "Reporting after Removal: Effects of Journalist Expulsion on Foreign News Coverage". What happened to coverage of China after a large portion of the reporting corps of @nytimes, @washingtonpost, @WSJ were expelled from China in 2020? 1/3
Share of stories about China did not change, nor did audience engagement with stories; sentiment of stories did not become more positive or negative; outlets did not become more likely to write stories because of actions or pronouncements by the Chinese government. 2/3
What appears to have changed was the production processes of outlets with expulsions--more articles were written collaboratively (increase in bylines and contribution credits). Paper at: academic.oup.com/joc/advance…. Replication dataverse.harvard.edu/datase…. 3/3
Jennifer Pan retweeted
I'm excited to share a new paper with @jenjpan and @mollyeroberts published in Science Advances: “Partisan conflict over content moderation is more than disagreement about facts”: doi.org/10.1126/sciadv.adg67… (open access) 1/9
Jennifer Pan retweeted
Excited to be presenting my research on misinformation exposure and effects for Democracy Day at Stanford with @jeffhancock @jenjpan @rutheappel @RyanMooreComm w/ @StanfordData. If you’re on campus, come by tomorrow (no classes for Democracy Day, so no excuse 😉)
