Tendency on power dynamics and social Identity through negative sentiment utterances - Ami Lia Calista; Ajar Pradika Ananta Tur (COMMICAST, 2025)
This paper investigates how political candidates of differing social status pragmatically employ sentiment in formal debate discourse, focusing on the 2024 U.S. Presidential Debate between Donald Trump and Kamala Harris. Political debates are rich in rhetorical strategies where sentiment influences persuasion and public perception, yet the pragmatic dimension of sentiment remains underexplored. To address this gap, the research integrates computational sentiment analysis with speech act classification to uncover how language choices fulfill rhetorical intentions. Using a mixed-method approach, VADER sentiment analysis was combined with manual categorization of speech acts based on Searle’s taxonomy. Debate transcripts were analyzed to quantify sentiment polarity and identify corresponding pragmatic functions. Results indicate that both candidates strategically used assertive, expressive, and commissive acts imbued with contrasting emotional tones. Trump frequently employed hyperbolic and affect-laden expressions to assert dominance and provoke response, whereas Harris relied on structured critique and historical references to convey accountability and moral authority. Sentiment functioned as a pragmatic resource for negotiating credibility, reinforcing social identity, and managing power relations. These findings highlight sentiment’s dual role as an emotional and rhetorical mechanism in high-stakes political communication. This study contributes to pragmatic and political discourse studies by demonstrating how negative sentiment utterances are systematically embedded within assertive, expressive, and commissive speech acts to negotiate power dynamics and construct social identity in formal political debates, while empirically extending speech act theory through the integration of computational sentiment analysis and qualitative pragmatic interpretation.