Summary of E2mocase: a Dataset For Emotional, Event and Moral Observations in News Articles on High-impact Legal Cases, by Candida M. Greco et al.
E2MoCase: A Dataset for Emotional, Event and Moral Observations in News Articles on High-impact Legal Cases
by Candida M. Greco, Lorenzo Zangari, Davide Picca, Andrea Tagarelli
First submitted to arxiv on: 13 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Digital Libraries (cs.DL); Physics and Society (physics.soc-ph)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces E2MoCase, a novel dataset designed to facilitate the integrated analysis of emotions, moral values, and events within legal narratives and media coverage. The authors recognize that media reports on legal cases can significantly shape public opinion, often embedding subtle biases that influence societal views on justice and morality. To address this challenge, they develop advanced models for emotion detection, moral value identification, and event extraction. By leveraging these models, E2MoCase offers a multi-dimensional perspective on how legal cases are portrayed in news articles. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a special dataset to help people understand how news reports on court cases can affect public opinion. It’s like analyzing the tone of a story to see if it’s biased or not. The researchers make special models that can detect emotions, identify values, and find important events in these stories. This helps us get a better sense of how court cases are reported in the news. |
Keywords
» Artificial intelligence » Embedding
