Hello! I am a senior data scientist at Code for America and a research fellow at the SNF Agora Institute and P3 Lab at Johns Hopkins University. I have a Ph.D. in political science from UC Berkeley, where I was a senior data science fellow at D-Lab. Since 2020, I have been working on the Mapping Modern Agora project (incubated at the SNF Agora) that utilizes big data and machine learning to map the U.S. civil society at scale. Prior to joining Code for America, I was an assistant professor of data science at the KDI School of Public Policy and Management in South Korea.

Research agenda

My research agenda lies at the intersection of political science, public policy, and data science. I use quantitative and mixed methods to examine what makes civic engagement, political participation, and policy implementation efficient and equitable. I investigate how these factors interact and shape the structure of policy governance. Additionally, I refine the measurements of identity and marginalization and study the variation of anti-immigrant politics and their resistance, as well as the political patterns of online harm and digital inequality. My regional focus is the United States, Canada, and East Asia.

Research pipeline

My work has been published in general science (e.g., Nature Scientific Data), political science (e.g., Perspectives on Politics [2x], Political Research Quarterly [2x], Studies in American Political Development, The ANNALS, and PS: Political Science and Politics) and computational social science journals and proceedings (e.g., Journal of Online Trust and Safety, Information Systems Frontiers, Journal of Computational Social Science, and ICWSM). My research has also appeared in popular outlets such as the Washington Post’s Monkey Cage and FiveThirtyEight.

I have two book projects. First, I am preparing a book version of my award-winning dissertation, tentatively titled “Demography Is Not Destiny: How Other Minorities Became Racial Groups.” Second, I am also working on a primer on civic data science, titled “Civic Data Handbook: 7 Ways to Reduce Discrimination and Increase Opportunities Using Data” (in Korean). This book will be published by Sejong Books in 2023.



Peer-reviewed journal articles

  1. “Validated Names for Experimental Studies on Ethnicity and Race.” (Charles Crabtree, Jae Yeon Kim, S. Michael Gaddis, John B. Holbein, Cameron Guage, and William Marx) Nature Scientific Data, Online First in March 2023 [replication]

  2. “Contested Identity and Prejudice Against Co-ethnic Refugees: Evidence from South Korea.” (Jae Yeon Kim and Taeku Lee) Political Research Quarterly, Online First in December 2022

  3. “Civil Society, Realized: Equipping the Mass Public to Express Choice and Negotiate Power.” (Hahrie Han+ and Jae Yeon Kim+) ANNALS of the American Academy of Political and Social Science, 2022, 699(1), 175-185

  4. “Teaching Computational Social Science for All.” (Jae Yeon Kim and Margaret Ng) PS: Political Science & Politics, 2022, 55(3), 605-609

  5. “Identity and Status: When Counterspeech Increases Hate Speech Reporting and Why.” (Jae Yeon Kim, Jaeung Sim, and Daegon Cho) Information Systems Frontiers, Online First in January 2022 [replication]

  6. “COVID-19 and Asian Americans: How Elite Messaging and Social Exclusion Shape Partisan Attitudes.” (Nathan Chan, Jae Yeon Kim, and Vivien Leung) Perspectives on Politics, Online First in December 2021 [replication]

  7. “Rewiring Linked Fate: Bringing Back History, Agency, and Power.” (Reuel Rogers+ and Jae Yeon Kim+) Perspectives on Politics, Online First in December 2021 [replication]

  8. “Misinformation and Hate Speech: The Case of Anti-Asian Hate Speech During the COVID-19 Pandemic.” (Jae Yeon Kim+ and Aniket Kesari+) Journal of Online Trust and Safety, 2021, 1(1) [replication]

  9. “Integrating Human and Machine Coding to Measure Political Issues in Ethnic Newspaper Articles.” (Jae Yeon Kim), Journal of Computational Social Science, 2021, 4(2), 585-612 [replication] (Winner of the 2020 Western Political Science Association Don T. Nakanishi Award)

  10. “How Other Minorities Gained Access: The War on Poverty and Asian American and Latino Community Organizing.” (Jae Yeon Kim), Political Research Quarterly, Online First in December 2020 [replication]

  11. “Racism Is Not Enough: Minority Coalition Building in San Francisco, Seattle, and Vancouver.” (Jae Yeon Kim), Studies in American Political Development, 2020, 34(2), 195-215 [replication]

Peer-reviewed conference and workshop proceedings

  1. “Intersectional Bias in Hate Speech and Abusive Language Datasets.” (Jae Yeon Kim, Carlos Ortiz, Sarah Nam, Sarah Santiago, and Vivek Datta), 2020, Proceedings of the Fourteenth International AAAI Conference on Web and Social Media (ICWSM), Data Challenge Workshop [replication]


  1. “A Three-Step Guide to Training Computational Social Science Ph.D. Students for Academic and Non-Academic Careers.” (Aniket Kesari+, Jae Yeon Kim+, Sono Shah+, Taylor Brown+, Tiago Ventura+, and Tina Law+) Revise and Resubmit at PS: Political Science & Politics

  2. “Unbundling Linked Fate: How Survey Respondents Interpret Linked Fate Question.” (Jae Yeon Kim and Alan Yan) [replication]

Book projects

Edited volume book chapters

  1. “Machines Do Not Decide Hate Speech: Machine Learning, Power, and the Intersectional Approach.” (Jae Yeon Kim) In C. Strippel, S. Paasch-Colberg, M. Emmer & J. Trebbe (Eds.), Challenges and perspectives of hate speech analysis, 2022, (pp. 261-275). Digital Communication Research (open-access book series by the German Communication Association)

Research briefs

  1. “Thanks to Trump’s Rhetoric, Asian Americans Are Moving Toward the Democratic Party.” (Nathan Chan, Jae Yeon Kim, and Vivien Leung), Washington Post’s Monkey Cage, March 30, 2021

  2. “The Three Tales of Chinatown: Why Racism Is Not Enough to Create a Race-based Coalition among Marginalized Groups.” (Jae Yeon Kim), UC Berkeley Canadian Studies Program, March 29, 2021

Public writing

  1. “Good Troublemakers Are the Key to Fixing Democracy in South Korea” (Jae Yeon Kim), Korea Pro, May 16, 2022.

  2. “Why Teaching Social Scientists How To Code Like A Professional Is Important.” (Jae Yeon Kim), UC Berkeley D-Lab, September 23, 2020

  3. “BAY-SICSS: Bridging Computational Social Scientists and Practitioners for Social Good.” (Jaren Haber, Jae Yeon Kim, and Nick Camp), Berkeley Institute of Data Science, September 15, 2020

  4. “Five Principles to Get Undergraduates Involved in Real-world Data Science Projects.” (Jae Yeon Kim), SAGE Ocean, June 24, 2020

  5. “How I Accidentally Became Interested in Data Science.” (Jae Yeon Kim), UC Berkeley D-Lab, February 24, 2020

Software development

I have developed open-source software that supports data curation.

  1. MapAgora: R package for getting tax reports, websites, and social media handles related to nonprofit organizations in the United States (with Milan de Vries)

  2. validatednamesr: R package for viewing, loading, and extracting the validated names for experimental studies on race and ethnicity datasets (with Charles Crabtree)

  3. autotextclassifier: R package for automatically classifying texts based on tidymodels (with Milan de Vries)

  4. tidytweetjson: R package for turning Tweet JSON files into a cleaned and wrangled dataset

  5. tidyethnicnews: R package for turning search results from the largest database on ethnic newspapers published in the United States (“Ethnic NewsWatch”) into a cleaned and wrangled dataset

Public datasets

  1. Validated Names for Experimental Studies on Ethnicity and Race (with Charles Crabtree, S. Michael Gaddis, John B. Holbein, Cameron Guage, and William Marx)

  2. Linked Fate Literature Review Dataset (1999-2019)

  3. Asian American and Latino Advocacy and Community Service Organizations Dataset (1868-2016)

Teaching and advising

I am an award-winning certified instructor and have taught computational social science in semester-long courses and short workshops. I have co-authored articles on making computational methods accessible to social scientists and helping social science Ph.D. students prepare for academic and non-academic data science careers. I wrote an open-access textbook for computational methods titled “Computational Thinking for Social Scientists.”

Community building

I love learning from other people who share similar research interests and building interdisciplinary communities. I have developed a large and growing network of collaborators across social sciences and engineering and co-organized the first partner location of the Summer Institute in Computational Social Science (SICSS) in the Bay Area (2020, co-hosted by UC Berkeley and Stanford) and South Korea (2022, co-hosted by KAIST and KDI School).



Here’s a summary of who I am: I was born and raised in South Korea, but I lived in Hong Kong and Taiwan by the time I finished college. While in college, I helped launch my alma mater’s first massive open online course project (KU OCW). I was also an activist for the Korean branch of Creative Commons, a digital rights advocacy organization, and served on the user service advisory board of Naver, South Korea’s largest internet company. After graduation, I worked as a strategy manager at a software startup in the Korean tech industry. I also authored a Korean book on how to make the most out of college, which sold more than 10,000 copies.

In 2014, I moved to the San Francisco Bay Area for my graduate studies and happily merged my four sides: an academic, a nerd, an entrepreneur, and an activist. When I’m not writing or coding, I enjoy listening to music, reading, cooking, drawing, and distance running.

To reflect on my life journeys, I’ve written several personal essays:

I also have a blog where I write about data science, social science, running, and self-management in Korean.

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