Partisan Event
Partisan events, defined as the selective inclusion or omission of events in news reporting to subtly influence public opinion, are a growing focus of research. Current studies utilize latent variable models and cross-article comparisons to detect these events, analyzing how media outlets, even those aiming for objectivity, exhibit bias through event selection. This research is significant because it reveals a nuanced form of media bias beyond overt language, impacting our understanding of how information shapes political attitudes and beliefs. Furthermore, the development of large language models capable of identifying and contextualizing partisan events is a key area of ongoing investigation.
Papers
All Things Considered: Detecting Partisan Events from News Media with Cross-Article Comparison
Yujian Liu, Xinliang Frederick Zhang, Kaijian Zou, Ruihong Huang, Nick Beauchamp, Lu Wang
Crossing the Aisle: Unveiling Partisan and Counter-Partisan Events in News Reporting
Kaijian Zou, Xinliang Frederick Zhang, Winston Wu, Nick Beauchamp, Lu Wang