Improving Language Models for Emotion Analysis: Insights from Cognitive Science - Laboratoire Interdisciplinaire des Sciences du Numérique
Communication Dans Un Congrès Année : 2024

Improving Language Models for Emotion Analysis: Insights from Cognitive Science

Résumé

We propose leveraging cognitive science research on emotions and communication to improve language models for emotion analysis. First, we present the main emotion theories in psychology and cognitive science. Then, we introduce the main methods of emotion annotation in natural language processing and their connections to psychological theories. We also present the two main types of analyses of emotional communication in cognitive pragmatics. Finally, based on the cognitive science research presented, we propose directions for improving language models for emotion analysis. We suggest that these research efforts pave the way for constructing new annotation schemes, methods, and a possible benchmark for emotional understanding, considering different facets of human emotion and communication.
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Dates et versions

hal-04624340 , version 1 (25-06-2024)
hal-04624340 , version 2 (03-07-2024)
hal-04624340 , version 3 (26-08-2024)

Identifiants

Citer

Constant Bonard, Gustave Cortal. Improving Language Models for Emotion Analysis: Insights from Cognitive Science. Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, Association for Computational Linguistics, Aug 2024, Bangkok, Thailand. pp.264-277. ⟨hal-04624340v3⟩
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