Beyond the Threat: Emotional Dimensions and Affective Intentions in YouTube Comments on Megathrust News

Muhammad Fikri Asysyamil

Authors

Muhammad Fikri Asysyamil Universitas Gadjah Mada

Keywords:

affective type, emotional dimension, megathrust, semantic component analysis, YouTube comment

Abstract

Background: The potential megathrust disaster in Indonesia has become a widely discussed issue following increased public attention to disaster warnings and related news coverage. YouTube comments reflect how netizens interpret disaster risks through language. However, previous studies have rarely examined how emotional dimensions relate to the communicative purposes underlying netizens' responses. Purpose: This study aims to identify the emotional dimensions and affective intentions represented in YouTube comments on news coverage of the potential megathrust disaster. Methods: A qualitative descriptive approach was applied to 479 comments from three YouTube news videos published in September 2026, selected through purposive sampling based on relevance, public attention, and variation in information presentation. The data were analyzed through domain and theme analysis, using semantic component analysis to identify lexical markers and semantic domains, followed by classification based on Scherer's semantic dimensional structure of emotion and affective types. Results: Negative-active emotions were dominant (262 comments), followed by positive-passive (100 comments), negative-passive (75 comments), and positive-active (42 comments), indicating that skepticism, criticism, and negative evaluation were frequently accompanied by tendencies toward action. Attitude was the most frequent affective type (349 comments), followed by interpersonal stance (259 comments) and mood (153 comments), whereas preference was rare and affect disposition was not identified. Conclusion: Netizens' comments functioned not only as emotional expressions but also as forms of social evaluation and positioning directed toward institutions and responsible actors. These findings contribute to a deeper understanding of language-based emotional representation in digital disaster communication.

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