2 citations · 5 across the 8 of their papers we have counts for
8 papers
Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter
Eun Cheol Choi, Emilio Ferrara
On social media, many users actively push back against false claims. Understanding who pushes back and how they do so matters, as this corrective activity is central to how misinfo…
Beyond the Mean: Three-Axis Fidelity for Aligning LLM-Based Survey Simulators from Small Pilot Data
Eun Cheol Choi, Youngrae Kim, Prabhu Pugalenthi +2
Large language models (LLMs) are increasingly used to simulate social survey responses, yet their outputs exhibit systematic biases: marginal distributions are skewed, response var…
RLHF May Not Reflect Genuine Preferences
Bijean Ghafouri, Eun Cheol Choi, Priyanka Dey +1
Reinforcement Learning from Human Feedback (RLHF) assumes that annotation responses reflect genuine human preferences. They often do not. Behavioral scientists have documented for…
The Traffickers' Pitch: Detecting Deceptive Recruitment in Online Job Boards
Siyi Zhou, Peiran Qiu, Tanishq Salkar +6
While substantial efforts in anti-trafficking research and practice have focused on identifying and assisting victims after exploitation occurs, comparatively less attention has be…
Mapping Election Toxicity on Social Media across Issue, Ideology, and Psychosocial Dimensions
Lei Cao, Wen Zeng, Xinyue Wu +2
Online political hostility is pervasive, yet it remains unclear how toxicity varies across campaign issues and political ideology, and what psychosocial signals and framing accompa…
Limited Effectiveness of LLM-based Data Augmentation for COVID-19 Misinformation Stance Detection
Eun Cheol Choi, Ashwin Balasubramanian, Jinhu Qi +1
Misinformation surrounding emerging outbreaks poses a serious societal threat, making robust countermeasures essential. One promising approach is stance detection (SD), which ident…
FACT-GPT: Fact-Checking Augmentation via Claim Matching with LLMs
Eun Cheol Choi, Emilio Ferrara
Our society is facing rampant misinformation harming public health and trust. To address the societal challenge, we introduce FACT-GPT, a system leveraging Large Language Models (L…
Automated Claim Matching with Large Language Models: Empowering Fact-Checkers in the Fight Against Misinformation
Eun Cheol Choi, Emilio Ferrara
In today's digital era, the rapid spread of misinformation poses threats to public well-being and societal trust. As online misinformation proliferates, manual verification by fact…