Jae Yeon Kim

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Advisors: 
Taeku Lee and Paul Pierson (co-chairs)
Subfields: 
Computational Social Science
Political Behavior
Race and Ethnic Politics
Personal Statement: 

I am a computational social scientist and a PhD candidate in Political Science at UC Berkeley. I am also a D-Lab Data Science Fellow, a Data Science Education Program Fellow at UC Berkeley, and a co-organizer of the Summer Institute in Computational Social Science in the San Francisco Bay Area (BAY-SICSS).

I use behavioral science, statistics, and data science tools to study how people think and behave with a focus on diversity and inclusion issues. Specifically, my research has focused on two questions: first, how minority group members experience racial bias (measurement) and second, how that affects the ways in which these people form political identities, attitudes, and behavior (causal inference). My dissertation applies computational, statistical, and qualitative methods to understand what unites racial minority groups in the United States. My dissertation research has received the Don T. Nakanishi Award for Distinguished Scholarship in Asian Pacific American Politics and part of it is forthcoming in Studies in American Political Development. My most recent research project investigates intersectional bias in hate speech and abusive language datasets and is forthcoming in Proceedings of the 2020 ICWSM Data Challenge on Safety.

I've taught computational social science at the graduate level as a lead instructor and data science at the undergraduate level as a co-instructor. I am passionate about making data science accessible.

To visit my website, click here.

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