2024/09/13 by Candida M. Greco, Greco, Candida M., Lorenzo Zangari +5 · 2 citations
Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Law #Computation and Language (cs.CL) #Computers and Society (cs.CY) #Digital Libraries (cs.DL) #FOS: Computer and information sciences #FOS: Physical sciences #Law, AI, and Intellectual Property #Legal Education and Practice Innovations #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.2409.09001
openalex publication_date 2024/09/13 · openalex created_date 2024/10/23 · openalex updated_date 2026/07/28
The way media reports on legal cases can significantly shape public opinion, often embedding subtle biases that influence societal views on justice and morality. Analyzing these biases requires a holistic approach that captures the emotional tone, moral framing, and specific events within the narratives. In this work we introduce E2MoCase, a novel dataset designed to facilitate the integrated analysis of emotions, moral values, and events within legal narratives and media coverage. By leveraging advanced models for emotion detection, moral value identification, and event extraction, E2MoCase offers a multi-dimensional perspective on how legal cases are portrayed in news articles.