Improving Language Models for Emotion Analysis: Insights from Cognitive Science

• URL: http://arxiv.org/abs/2406.10265v2
• Date: Mon, 26 Aug 2024 10:54:12 GMT
• Title: Improving Language Models for Emotion Analysis: Insights from Cognitive Science
• Authors: Constant Bonard, Gustave Cortal,
• Abstract summary: We present the main emotion theories in psychology and cognitive science. We introduce the main methods of emotion annotation in natural language processing. We propose directions for improving language models for emotion analysis.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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