TY - GEN
T1 - Moving Beyond Stance Detection in Cross-Cutting Communication Analysis
AU - Rezapour, Rezvaneh
AU - Delgado Ramos, Daniela
AU - Jeoung, Sullam
AU - Diesner, Jana
N1 - Acknowledgment. This work was supported in part by the Cline Center for Advanced Social Research at the University of Illinois Urbana-Champaign, including a Linowes Fellowship.
PY - 2023
Y1 - 2023
N2 - 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.)
AB - 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.)
KW - Contextual analysis
KW - Cross-cutting communication
KW - Stance Analysis
UR - http://www.scopus.com/inward/record.url?scp=85173274277&partnerID=8YFLogxK
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U2 - 10.1007/978-3-031-43129-6_30
DO - 10.1007/978-3-031-43129-6_30
M3 - Conference contribution
AN - SCOPUS:85173274277
SN - 9783031431289
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 305
EP - 315
BT - Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Proceedings
A2 - Thomson, Robert
A2 - Al-khateeb, Samer
A2 - Burger, Annetta
A2 - Park, Patrick
A2 - A. Pyke, Aryn
PB - Springer
T2 - 16th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2023
Y2 - 20 September 2023 through 22 September 2023
ER -