E2MoCase: A Dataset for Emotional, Event and Moral Observations in News Articles on High-impact Legal Cases
This addresses the need for holistic analysis of media bias in legal reporting, but it is incremental as it primarily offers a new dataset without novel methodological breakthroughs.
The authors tackled the problem of analyzing biases in media coverage of legal cases by introducing E2MoCase, a dataset that integrates emotional tone, moral framing, and events, but no concrete results or numbers are provided.
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.