Jaehong Kim
Moral Emotion · Attention Economy · Machine Behavior
I am a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), advised by sociologist Wonjae Lee. I completed two research internships at the Max Planck Institute for Security and Privacy (MPI-SP), supervised by computational social scientist Meeyoung Cha, with whom I continue to collaborate. My research is supported by the Hyundai Motor Chung Mong-Koo Foundation. Beyond academia, my research on foreign-linked influence operations has received national media coverage, including an SBS News report with over 1.2 million views, and has contributed to policy discussions among lawmakers.
News
- Aug 2026 Paper accepted to IMC 2026 Nothing to Dread: A Measurement Study of a Dark Web Social Forum
- Jun 2026 Paper accepted to USENIX Security 2026. 🇺🇸 See you in Baltimore! Cross-National Information Attacks: A Two-Decade Analysis of Troll Behavior in Korea
- Apr 2026 Paper accepted to ACL 2026 (Findings) Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions
- Feb 2026 🇰🇷 Returned to KAIST after internship at MPI-SP
- Jan 2026 Paper accepted to WWW 2026 Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the US
- Sep 2025 Paper accepted to EMNLP 2025 (Findings) Parallel Communities Across the Surface Web and the Dark Web
- Sep 2025 🇩🇪 Started internship at MPI-SP
- Nov 2024 🇰🇷 Returned to KAIST after internship at MPI-SP
- Sep 2024 🇩🇪 Started internship at MPI-SP
- Apr 2024 Paper accepted to ACL 2024 (Findings) How Do Moral Emotions Shape Political Participation? A Cross-Cultural Analysis of Online Petitions Using Language Models
Research
My research examines how moral emotions shape human and machine behavior.
Human Behavior. I build multimodal frameworks that detect moral emotions in English and Korean text and images. My findings show that moral outrage (anger at perceived wrongdoing) most strongly predicts committed user participation and is disproportionately used by suspected foreign-linked trolls.
Machine Behavior. I study how large language models internally represent moral outrage. Steering these representations causally shifts punishment judgments, leading models to recommend harsher sentences for identical offenses.
Publications
-
Nothing to Dread: A Measurement Study of a Dark Web Social Forum
-
Cross-National Information Attacks: A Two-Decade Analysis of Troll Behavior in Korea
-
Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions
-
Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the US
-
Parallel Communities Across the Surface Web and the Dark Web
-
How Do Moral Emotions Shape Political Participation? A Cross-Cultural Analysis of Online Petitions Using Language Models
Ongoing Work
-
Investigating the Causal Role of Internal Moral Outrage in LLM Punishment JudgmentsUnder Review
-
Effects of online moral emotion on offline protest behaviorOngoing
-
Explainable moral emotion classifierOngoing
Education
-
Ph.D. Candidate, Culture TechnologyKAIST · Social Computing LabExpected Feb 2027
-
M.S., Culture TechnologyKAIST · Social Computing LabBridging social psychology theory and AI methodology2023
-
B.A., Communication & Psychology · Minor in ICT Convergence · cum laudeHandong Global University · Data Analysis LabI came to believe learning is meant to be shared.2021