Turn-Taking and Adjacency Pairs in X/Twitter Threads: Analyzing Public Outcry Regarding the DPR Dissolution Discourses
DOI:
https://doi.org/10.21009/ijlecr.v12i1.67789Keywords:
Conversation Analysis, Digital Political Communication, Interactional Structure, Public Outcry, X/Twitter ThreadsAbstract
In the digital era, social media platforms like X/Twitter have emerged as primary arenas for political contestation and public discourse. While previous studies have extensively explored the thematic content of political sentiments, there is a noticeable research gap regarding the microscopic structural mechanisms of these interactions during high-stakes political unrest. Specifically, how conversational structures facilitate the escalation of public outcry remains under-examined within the context of the Indonesian legislative crisis. This study investigates the dynamics of public discourse surrounding the potential dissolution of the Indonesian House of Representatives (DPR) by analyzing the interactional architecture of online communication. Employing a qualitative framework grounded in Conversation Analysis (CA), the research scrutinizes turn-taking systems and adjacency pairs, such as question-answer and complaint-response, within purposively selected X/Twitter threads. The findings reveal that conversational structures are not merely neutral containers for information; rather, the formation of agreement and the articulation of dissent are heavily dictated by the perceived legitimacy of information and the authority of the interactants. The analysis shows that emotional appeals frequently disrupt standard adjacency expectations, leading to rapid escalations of public outcry through complex, branching conversational sequences. This study concludes that the structural organization of digital talk is fundamental to the construction of collective political sentiment. This research contributes to the field of digital political communication and forensic linguistics by offering a nuanced methodology for dissecting complex online social interactions.
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