Deciphering Children's Social Cognition: Leveraging NLP for Deeper Insights Into Social Role Perceptions - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Deciphering Children's Social Cognition: Leveraging NLP for Deeper Insights Into Social Role Perceptions

Résumé

This research uses natural language processing (NLP) methods to explore how children of varying genders and ages perceive social roles. By analyzing interview responses from 184 first- and fifth-grade French children, the study investigates their thoughts and beliefs about the concept of “friend.” Through a specialized NLP technique, the study categorizes the most common lemmas, revealing three main themes: similarity, support/intimacy, and association/affection. Statistical analyses of these patterns provide a deeper understanding of how children comprehend and interpret this social role. This research offers a unique perspective by focusing on the children's viewpoint, which contrasts with studies that mainly reflect the adult perspective.
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Dates et versions

hal-04738858 , version 1 (15-10-2024)

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Citer

Farida Saïd, Jeanne Villaneau. Deciphering Children's Social Cognition: Leveraging NLP for Deeper Insights Into Social Role Perceptions. 2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Jul 2024, Guangzhou, China. pp.1-6, ⟨10.1109/ICNC-FSKD64080.2024.10702313⟩. ⟨hal-04738858⟩
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