I am an Assistant Research Scholar (postdoctoral fellow) at the SNF Agora Institute at Johns Hopkins University. I study computational social science, measurement and data collection, racial and ethnic politics, political behavior, political geography, and civic engagement. In Spring 2022, I will join the KDI School of Public Policy and Management as an Assistant Professor of Data Science. I received my Ph.D. in political science from UC Berkeley, where I was a Senior Data Science Fellow at D-Lab.
My research centers around two themes: (1) advancing social science theory and methods on the politics of marginalization, and (2) making social science research more efficient and scalable. I pursue these themes through wide-ranging projects that share a common objective: formalizing and validating the experience of those in the margins of the social hierarchy. To produce this type of knowledge systematically, I critically use quantitative and computational methods, often in conjunction with qualitative methods.
My research has been published by or is forthcoming at many journals, including Perspectives on Politics [2x], Political Research Quarterly, and Studies in American Political Development, among others. My work has also appeared in popular outlets such as the Washington Post’s Monkey Cage. I am the recipient of the Western Political Science Association’s 2020 Don T. Nakanishi Award for distinguished scholarship in Asian Pacific American Politics.
I have developed open-source software that supports data curation and taught computational social science in semester-long courses and short workshops. I am a co-developer of MapAgora, an R package that helps collect, process, and combine various data on U.S. nonprofits at scale. I am currently working on an open textbook project titled “Computational Thinking for Social Scientists."
I love learning from other people who share similar research interests. I have developed a large and growing network of collaborators across social sciences and engineering. I am also deeply interested in promoting collaboration between researchers and civil society actors. I co-organized the BAY-SICSS to bridge computational social scientists and nonprofits for social good. Please do not hesitate to get in touch via sending me an email at email@example.com.
PhD in Political Science, 2021
Nathan Chan, Jae Yeon Kim, and Vivien Leung. Thanks to Trump’s Rhetoric, Asian Americans Are Moving Toward the Democratic Party. Washington Post’s Monkey Cage. March 30, 2021
Jae Yeon Kim. The Three Tales of Chinatown: Why Racism Is Not Enough to Create a Race-based Coalition among Marginalized Groups. UC Berkeley Canadian Studies Program. March 29, 2021
Kim, Jae Yeon. Why Teaching Social Scientists How To Code Like A Professional Is Important. UC Berkeley D-Lab. September 23, 2020.
Haber, Jaren, Jae Yeon Kim, and Nick Camp. BAY-SICSS: Bridging Computational Social Scientists and Practitioners for Social Good. Berkeley Institute of Data Science. September 15, 2020.
Kim, Jae Yeon. Five Principles to Get Undergraduates Involved in Real-world Data Science Projects. SAGE Ocean. June 24, 2020.
Kim, Jae Yeon. How I Accidentally Became Interested in Data Science. UC Berkeley D-Lab. February 24, 2020.
Here is the list of software and data, which I have created for other researchers and practitioners.
MapAgora: R package for getting tax reports, websites, and social media handles related to nonprofit organizations in the United States (with Milan de Vries)
autotextclassifier: R package for automatically classifying texts based on tidymodels (with Milan de Vries)
tidytweetjson: R package for turning Tweet JSON files into a cleaned and wrangled dataset.
tidyethnicnews: R package for turning search results from one of the largest databases on ethnic newspapers and magazines published in the United States into a cleaned and wrangled dataset.
rnytapi: R interface for the New York Times API
tidybibtex: R package for tidying BibTeX files
p3themes: R package for applying p3 lab themes to ggplot2 objects (with Grace Park and Liz McKenna)
Instructor, D-Lab, UC Berkeley, Summer 2020-Fall 2020
Co-instructor, Data Science Discovery Team Lead Seminar, Division of Computing, Data Science, and Society, UC Berkeley, Spring 2020
I believe that collaboration makes me a better researcher and research more fun. I have researched with 32 amazing people across social sciences and engineering.
The following is the list of my collaborators’ names, fields, and affiliations (ordered alphabetically). Please check out their websites to learn more about their research.
I was born and raised in South Korea, but I had also lived in Hong Kong and Taiwan by the time I finished college. I moved to the San Francisco Bay Area in 2014 as a graduate student in political science at UC Berkeley. Before my graduate studies, I worked in the tech industry in South Korea. I was a strategy manager at a software startup and served on the advisory board of Naver, “The Google of South Korea.”
I am a first-generation college student and grew up in a working-class family. My late father was a factory worker of 32 years at a paper mill, and my mother was a housekeeper. Yet, despite their humble educational backgrounds, they loved and valued learning. My supportive parents and numerous mentors put me on the path to be where I am today. To pay forward the generosity I have received, I am committed to increasing the pipeline of diverse talent in academia.
When I do not write or code, I enjoy cooking, hiking, and distance running. I ran my first half marathon on September 19, 2021 (the San Francisco Marathon) in time 2:03:26. I am also an avid reader and music enthusiast.
2021 San Francisco Marathon