Annie Y. Chen

Annie Y. Chen

Data Scientist

Institute for State and Local Governance

Hi! I am a data scientist at the CUNY Institute for State and Local Governance where I support the work of the NYPD Monitor and the NYPD Reform and Reinvention Collaborative. Before moving to New York, I was a quantitative social science researcher at Dartmouth College and a Bright Line Watch Fellow. I graduated with a Master’s degree in Political Science from McGill University in Montréal, Canada. I enjoy wrestling with social science questions.


  • Criminal justice reform
  • Online information consumption
  • Voting systems and voting behavior
  • Causal inference


  • MA in Political Science, 2020

    McGill University

  • BA in Political Science; Criminology, 2017

    University of Toronto


Subscriptions and external links help drive resentful users to alternative and extremist YouTube channels

Do online platforms facilitate the consumption of potentially harmful content? Using paired behavioral and survey data provided by participants recruited from a representative sample in 2020 (n = 1181), we show that exposure to alternative and extremist channel videos on YouTube is heavily concentrated among a small group of people with high prior levels of gender and racial resentment. These viewers often subscribe to these channels (prompting recommendations to their videos) and follow external links to them. In contrast, nonsubscribers rarely see or follow recommendations to videos from these channels. Our findings suggest that YouTube’s algorithms were not sending people down “rabbit holes” during our observation window in 2020, possibly due to changes that the company made to its recommender system in 2019. However, the platform continues to play a key role in facilitating exposure to content from alternative and extremist channels among dedicated audiences.

Like-minded sources on Facebook are prevalent but not polarizing

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.

Discriminatory Immigration Bans Elicit Anti-Americanism in Targeted Communities: Evidence from Nigerian Expatriates (Journal of Experimental Political Science)

Do discriminatory US immigration policies affect foreign public opinion about Americans? When examining negative reactions to US actions perceived as bullying on the world stage, existing research has focused either on US policies that involve direct foreign military intervention or seek to influence foreign countries’ domestic economic policy or policies advocating minority representation. We argue that US immigration policies – especially when they are perceived as discriminatory – can similarly generate anti-American sentiment. We use a conjoint experiment embedded in a unique survey of Nigerian expatriates in Ghana. Comparing respondents before and after President Trump surpisingly announced a ban on Nigerian immigration to the United States, we find a large drop (13 percentage points) in Nigerian’s favorability towards Americans.