Human and AI Alignment on Stance Detection

Media reporting and public opinion polls following the assassination of UnitedHealthcare CEO Brian Thompson suggested a surprising degree of support for the suspect Luigi Mangione, lack of empathy for the victim, and antipathy towards the health insurance industry. The goal of our project is to examine the social media discourse following the assassination to see whether the mainstream media reporting on this event was accurate and to examine key themes and conflicts in public discourse that emerged on social media. This poster reports the preliminary findings from the stance detection task using Large Language Models (LLMs) and human annotation. We report X users’ stance on Luigi Mangione (In-Favor, Neutral, and Against), and provide interpretation on “In-Favor” and “Against” stances. Further, we report evaluation results on human-human agreement, and human-AI agreement. Our findings and discussion contribute to developing better prompt design for fine-tuning and also guide social scientists in adopting LLMs for stance detection using social media data.

Authors

Institutions

Publication Details

Journal
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Published
2025-05-14
DOI
https://doi.org/10.32473/flairs.38.1.138976
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Human and AI Alignment on Stance Detection

Nic DePaula, Lingyao Li, Loni Hagen, Astrid Hagen et al.
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Sentiment Analysis and Opinion Mining
article

Human and AI Alignment on Stance Detection

Nic DePaula, Lingyao Li, Loni Hagen, Astrid Hagen, Aaron Fox, Daniel Tafmizi, Christopher Reddish
article en

Abstract

Media reporting and public opinion polls following the assassination of UnitedHealthcare CEO Brian Thompson suggested a surprising degree of support for the suspect Luigi Mangione, lack of empathy for the victim, and antipathy towards the health insurance industry. The goal of our project is to examine the social media discourse following the assassination to see whether the mainstream media reporting on this event was accurate and to examine key themes and conflicts in public discourse that emerged on social media. This poster reports the preliminary findings from the stance detection task using Large Language Models (LLMs) and human annotation. We report X users’ stance on Luigi Mangione (In-Favor, Neutral, and Against), and provide interpretation on “In-Favor” and “Against” stances. Further, we report evaluation results on human-human agreement, and human-AI agreement. Our findings and discussion contribute to developing better prompt design for fine-tuning and also guide social scientists in adopting LLMs for stance detection using social media data.

Proceedings of the ... International Florida Artificial Intelligence Research Society ConferenceVol. 38
University of South Florida (US), University at Albany, State University of New York (US), SUNY Polytechnic Institute (US)
Openalex Percentile: Top 70%
Sentiment Analysis and Opinion Mining
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.