Haewoon Kwak

Misinformation and Its Impacts Complex Network Analysis Techniques Social Media and Politics Opinion Dynamics and Social Influence Hate Speech and Cyberbullying Detection

Publications

226

Citations

14,569

Est. group size

—

Recurring co-author estimate

Active years

Publishing since 1977

Research summary

AI-generated

Haewoon Kwak studies how people and artificial intelligence systems interact around online information, opinions, and social behavior. Recent work focuses heavily on large language models (LLMs)—examining their biases, moral and political reasoning, cross-cultural differences, and how they collaborate or influence people. Earlier and ongoing themes include misinformation, social media and politics, and detecting harmful online content such as hate speech.

Large language model behavior and biasMisinformation and social media analysisOpinion dynamics and political discourseCross-cultural and health-related text analysisHuman-AI interaction and collaboration

Publication activity was steady at roughly 15-20 papers per year through the late 2010s, dipped around 2024-2025, and shows a marked increase in 2026 driven largely by work on large language models.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence

Publications per year over the last 10 years — averaging 14.4/year recently

Recent publications

Vulnerability of LLMs' Stated Beliefs? LLMs Belief Resistance Check Through Strategic Persuasive Conversation Interventions
Open MIND · 2026
XChoice: Explainable Evaluation of AI-Human Alignment in LLM-based Constrained Choice Decision Making
arXiv (Cornell University) · 2026
XChoice: Explainable Evaluation of AI-Human Alignment in LLM-based Constrained Choice Decision Making
arXiv (Cornell University) · 2026
Vulnerability of LLMs' Stated Beliefs? LLMs Belief Resistance Check Through Strategic Persuasive Conversation Interventions
arXiv (Cornell University) · 2026
Zero-shot stance detection in practice: insights on training, prompting, and decoding with a capable lightweight LLM
PeerJ Computer Science · 2026
Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing
JMIR Formative Research · 2026
LLMs Can Infer Political Alignment from Online Conversations
arXiv (Cornell University) · 2026
LLMs Can Infer Political Alignment from Online Conversations
arXiv (Cornell University) · 2026
Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
arXiv (Cornell University) · 2026
Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
arXiv (Cornell University) · 2026
SynSym: A Synthetic Data Generation Framework for Psychiatric Symptom Identification
arXiv (Cornell University) · 2026
CogBias: Measuring and Mitigating Cognitive Bias in Large Language Models
arXiv (Cornell University) · 2026
CogBias: Measuring and Mitigating Cognitive Bias in Large Language Models
arXiv (Cornell University) · 2026
If I Change Your Eyes, Are You Still You? Identity Thresholds in Deepfake Perception
2026
When Behavior Is Not Enough: Identity Biases in Human-AI Creative Collaboration
2026

Publishes in

arXiv (Cornell University)×56
Proceedings of the International AAAI Conference on Web and Social Media×17
Zenodo (CERN European Organization for Nuclear Research)×5
Lecture notes in computer science×4
Scientific Reports×3

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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