Book chapter
Moving Beyond Stance Detection in Cross-Cutting Communication Analysis
Social, Cultural, and Behavioral Modeling
01 Jan 2023
Abstract
In today’s social media landscape, personal opinions on controversial topics are widespread. While some platforms provide structured environments for discussing such matters, fostering cross-cutting communication among individuals, understanding how people engage in these discussions remains a challenge. This study aims to understand the dynamics of discussing controversial topics, focusing specifically on the topic of abortion. Using an aspect-based approach, we employ BERT-based topic modeling and attention mechanisms to identify key aspects of debates. Through clustering, we identify highly polarizing aspects and examine the contextual nuances and sentiment surrounding them. Our methodology enhances our understanding of cross-cutting communication on controversial topics and offers an in-depth analysis of consensus and disagreement among participants. Our study contributes to the field of stance analysis, revealing opportunities for mutual understanding and uncovering diverse perspectives on controversial issues. (Warning:this paper contains content that may be triggering.)
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Details
- Title
- Moving Beyond Stance Detection in Cross-Cutting Communication Analysis
- Creators
- Rezvaneh Rezapour - Drexel UniversityDaniela Delgado RamosSullam Jeoung - University of Illinois Urbana-ChampaignJana Diesner - University of Illinois Urbana-Champaign
- Publication Details
- Social, Cultural, and Behavioral Modeling
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland; Cham
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Scopus ID
- 2-s2.0-85173274277
- Other Identifier
- 991021861828404721