Hi! I’m a Royster fellow and a Richard Cole fellow at the Hussman School of Journalism and Media, Univeristy of North Carolina at Chapel Hill. My advisor is Dr. Shannon McGregor. I’m also a graduate affiliate with the Center for Information, Technology, and Public Life (CITAP). Previously, I worked at SNU FactCheck Center, the first and only fact-checking platform in South Korea.
I’m on the academic job market for 2023-24!
Transnational platform ecosystems harm children and women outside the West. in Tech Policy Press (2022)
AI chatbot systems can harm users in several ways. in Slate (2021)
Ph.D. in Communication, Expected 2024
University of North Carolina at Chapel Hill, USA
M.A. in Communication, 2018
Seoul National University, South Korea
B.A. in Media and Mass Communication, 2016
Korea University, South Korea
R, Python, SQL | SPSS, STATA, Qualtrics, MTurk
survey, experiment, content analysis, statistical analysis
interview/focus-group, textual analysis, grounded theory
A mass sex trafficking crime that happened in South Korea was only possible with the use of the combined affordances of several Internet platforms and cloud storage providers, the majority of which are headquartered in the West.
We investigate what drives Americans’ opinions on whether the government, platforms, or individual users should be responsible for social media content. Using data from a nationally representative survey of over 10,000 Americans, we show how anti-establishment beliefs and beliefs in individualism may drive people to put the onus on individual users to bear the responsibility for online content.
A recent incident of personal data misuse in South Korea provides us a clear picture of what can go wrong, and how consumers can fight back.
We propose a new model that explains the gap between how AI companies and the public understand organizational crises caused by AI systems. How does a crisis of an AI company become scandalized? We use the case of a South Korean AI company, Scatterlab, to answer this question.
I conducted an online survey to understand the different motivations, privacy concern levels, and privacy behaviors among different types of users and non-users of Tik Tok. Including active users, silent users, former users, and non-users, data were collected through an online survey of 266 respondents.