Dataset of userʼs emotional reactions to news articlesZenodo

Abstract

This paper presents a dataset of news articles collected from several Mexican news sources and users' emotional reactions to these news articles. Users were presented with the collected news and, after reading it, were asked to indicate the emotion it provoked in them. The emotions considered were happy, surprised, inspired, moved, neutral, sad, fearful, and angry. This dataset offers a particular focus on emotional reactions from the readerʼs perspective and has great potential for use in sentiment analysis, linguistics, and media studies research. Furthermore, the news is in Spanish which is a language where resources of this type are scarce. The detailed data collection methodology provides a solid foundation for future research and development in emotion-aware news recommendation systems.

Keywords

• News articles
• Emotion detection
• Affective computing
• News recommendation system