乔·拜登和唐纳德·特朗普在政治辩论中会话特征的比较

Lina Shofiah, Hendi Pratama, Henrikus Joko Yulianto
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引用次数: 0

摘要

会话分析用于通过考虑制度设置或情况来识别交互中特征的使用。在这里,政治局势是由于控制局势的条件必须不同而使用的。本研究旨在比较乔·拜登和唐纳德·特朗普在2020年美国总统大选最后一场辩论中使用的对话特征。这是一项使用Schegloff(1974)提出的会话分析方法的定性研究。数据分析基于会话特征,包括轮流策略,邻接对和修复。结果发现,两位候选人使用的会话特征有一些相似之处,也有一些差异。相似之处表明,两位说话者都更喜欢使用所有的轮流策略、第一和第二对零件的类型以及修复策略。此外,在使用会话特征的数量上也发现了差异。唐纳德·特朗普可能会使用更多的特征,因为他在辩论中使用了更多的轮转策略。总而言之,在政治环境中,人们倾向于更多地轮流分享自己的想法并回应对方。它会影响另一个会话特征的使用,包括使用它们的频率。此外,在政治情境中使用三个特征进行比较的结果成为本研究的新颖性,因为这一情境在会话分析中是一个罕见的话题。这一结果也有助于丰富未来研究的参考,特别是在政治环境中使用会话分析。
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The Comparison of Conversational Features Used by Joe Biden and Donald Trump in Political Debate
Conversation analysis is used to identify the use of features in an interaction by considering the institutional settings or situation. Here, political situation is used because of the condition of controlled situation must be different. This study aimed to compare the conversational features used by Joe Biden and Donald Trump in the final presidential election debate of America in 2020. This was a qualitative study using the conversational analysis approach proposed by Schegloff (1974). The data were analyzed based on the conversational features used including turn-taking strategies, adjacency pairs, and repairs. The results found there were some similarities and differences of conversational features used by both candidates. The similarities showed both speakers preferred to use most of all turn-taking strategies, types of first and second-pair parts, and repair strategies. Besides, the differences were found in the number of conversational features used. Donald Trump tent to use more features since he used more turn-taking strategy to take the turn during the debate. In sum, in political setting, people tend to take more turn to share their idea and respond the other. It affects the use of another conversational features including the frequency of using them. Furthermore, the result of comparing using three features in a political situation becomes the novelty of this research since this setting is a rare topic in conversation analysis. This result is also contributed on enriching references of future research using conversation analysis specifically in a political setting.
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发文量
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审稿时长
24 weeks
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