在工业4.0时代中，媒介生态发生变革，社交媒体的出现冲击了传统的报纸、广播、电视在政治传播中的主流话语权和信息传播的主导地位，政治媒介化与媒介政治化的趋势颠覆了单向的政治传播模式。推特作为最热门的社交媒体平台之一，凭借大数量、高活跃度的用户成为了政治传播中的理想工具。推特政治传播在特朗普时代达到了巅峰，影响着选举结果甚至政治决策。 社交媒体给政治传播提供新场域的同时，也给情感的快速广泛传播提供了条件，推特政治传播受到情感的裹挟。在后真相时代中，情感代替观点与真相广泛传播成为常态，改变了政治传播的路径。因此，传播学分析视角已经不足以对情感作用下的政治传播进行全面的分析，本研究引入情感社会学视角对特朗普推特政治传播进行研究。 本研究通过定量研究与定性研究相结合的方式对特朗普推文情感对受众传播行为的影响进行测量与计算，以探究情感对于政治传播的影响。主要研究方法为文本情感分析法，使用计算机文本分析工具LIWC对特朗普推文进行客观的情感分析。通过分析发现特朗普推文的情感是一个多维度可测量的结构。将LIWC中的13个情感参数与PAD模型中的愉悦度（P）、唤醒度（A）以及支配度（D）进行对应，随后将LIWC情感参数与特朗普推文的转发、评论、点赞作为观测变量，搭建情感与受众传播行为的预设模型，以探究情感三个维度对受众传播行为的影响，并通过相关性分析与主成分分析等方法对模型进行修正与检验。 通过验证发现模型成立，情感的愉悦度、唤醒度和支配度均与受众传播行为存在显著的相关性，但愉悦度与受众传播行为的线性相关不显著。使用情感社会学的互动仪式理论、情感社会结构理论与情感交换理论对模型结果进行解释。最后，根据特朗普推文情感与受众行为关系的最终模型以及情感社会学理论对情感作用下的特朗普推特政治传播路径进行重构。

In the era of Industry 4.0, the discourse power and dominant position once possessed by traditional media in political communication are impacted by the reformed ecology of media and the emergence of social media. As one of the most popular social media platforms, Twitter has become an ideal tool in political communication. The political communication on Twitter is reaching its peak in the Trump era, influencing elections and even political decisions. As a result, the Trump’s Twitter is adopted as the object of the study. Social media provides a new field for political communication, which also lays foundation for the dissemination of emotions. In the post-truth era, the widespread emotions is changing the path of political communication. Therefore, the study introduces the sociology theories of emotion to analyze the Trump’s political communication on Twitter under the influence of emotions. This research aims to measure the impact of the affective factors in Trump's tweets on audience behavior, adopting quantitative research. Computerized sentiment analysis is the main research method while LIWC is applied as the tool. Based on the research, it can be found that the sentiment in Trump’s tweets is a multi-dimensional measurable structure. 13 affective variables in LIWC are matched with the three dimensions of the PAD emotional state model, namely pleasure (P), arousal (A) and dominance (D). Then a default model of emotion and audience behavior is built with Amos 26.0 to investigate how the three dimensions of emotion influence the audience behavior. Correlation analysis and principal component analysis are applied to modify and verify the model. It is found in the research that the level of pleasure, arousal and dominance all have a significant correlation with the audience behavior on Twitter, but the linear correlation between pleasure and audience behavior is not significant. Interaction ritual theory, the theory of social structure and the emotional exchange theory are adopted to explain the results. Finally, the path of political communication on Twitter influenced by emotion is reconstructed.