E2MoCase: A Dataset for Emotional, Event and Moral Observations in News Articles on High-impact Legal Cases

TL;DR

E2MoCase is a new dataset that enables comprehensive analysis of emotional tone, moral framing, and events in news articles about high-impact legal cases, aiding understanding of media bias and societal influence.

Contribution

The paper introduces E2MoCase, a novel multi-dimensional dataset for analyzing emotions, morals, and events in legal news coverage, integrating advanced NLP models.

Findings

E2MoCase facilitates detailed analysis of media bias in legal reporting.

The dataset supports improved detection of emotional and moral cues in news articles.

It enables better understanding of societal perceptions of justice and morality.

Abstract

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.