Emotion detection using natural language processing
The analysis of human emotions is of great interest in data analysis, as it allows us to identify patterns and behaviors in people. Different techniques are used, such as linguistic rule-based approaches. Natural language processing (NLP) is a branch of AI that seeks to make machines understand language like humans do. It combines computational linguistics with machine learning and deep learning models. In emotional prosody, spoken words convey linguistic and paralinguistic information, where the emotional context influences the interpretation of the words. Alexithymia refers to difficulty identifying and expressing emotions. AI and NLP offer powerful tools for their study and application, which is why it was possible to develop an AI for the detection of emotions through natural language, resulting in a system that offers sentiment analysis for patients.
Authors
- María del Carmen Santiago Díaz
- Ana Claudia Zenteno Vázquez
- A Núñez
- Judith Pérez Marcial
- Gustavo Trinidad Rubín Linares
Institutions
- Benemérita Universidad Autónoma de Puebla (MX)
Publication Details
- Journal
- International Journal of Combinatorial Optimization Problems and Informatics.
- Published
- 2024-11-29
- DOI
- https://doi.org/10.61467/2007.1558.2024.v15i5.564
- Citations
- 1
- Primary Topic
- Emotion and Mood Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.51