<![CDATA[Emotional prosody plays an important role in expressing emotions during spontaneous speech. However, studies on livestream communication have primarily focused on audience engagement and viewer interaction, while emotional prosody produced by streamers remains underexplored. Therefore, this study investigates emotional prosody manifested in eaJ’s spontaneous speech during an Among Us livestream and examines how interactions with other players create variations in emotional expression. This study employed a descriptive qualitative approach within a psycholinguistic framework. The data were obtained from an Among Us livestream uploaded on the eaJ Stream Archive YouTube channel. Fourteen excerpts containing emotional reactions were selected and analyzed using Juslin and Laukka’s (2003) emotional prosody framework. Fourteen excerpts were selected from all rounds of the livestream based on the salience of emotional expression and the absence of recurring prosodic patterns, as eaJ was frequently eliminated early in each round through being killed or voted out, resulting in limited interaction per round despite the overall duration of over four hours.The findings revealed five types of emotional prosody: anger, happiness, surprise, sadness, and fear. Anger emerged as the most dominant emotional category, while emotional variations appeared to be associated with interactional contexts such as accusations, voting discussions, humorous exchanges, and unexpected gameplay events. The findings also indicate that emotional meaning was conveyed through prosodic features, including pitch, loudness, stress, speech rate, and intonation, supported by visual cues such as facial expressions and body movements. This study concludes that emotional prosody functions as a dynamic communicative resource for expressing emotions during real-time interaction and contributes to psycholinguistic research on language and emotion in digital communication. Future research may examine emotional prosody across different gaming genres, livestream platforms, and interactional settings to provide a broader understanding of emotional expression in digital communication.]]>
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