Valle-Cruz, D., Sandoval-Almazán, R., & López-Chau, A. (2023). Affective Polarization in the US: Multi-Emotional Charge Analyzed Through Affective Computing. In Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media (pp. 192-219). IGI Global.

DOI: 10.4018/978-1-6684-6242-3.ch010.

Abstract: Affective polarization is a phenomenon that has invaded the political arena empowered by social networks. In this chapter, the authors analyze the Capitol riot posts on Twitter. The authors use affective computing to achieve this, introducing the multi-emotional charge and statistical analysis based on the t-student test and Welch’s t-test. The research questions guiding this study are: How do social media platforms’ messages impact inciting? Do social media platforms’ messages with negative emotional charges affect legitimizing of the Capitol protest? Findings identify the significant influence of Donald Trump on Twitter during the Capitol riot. Moreover, data analysis identifies positive and negative emotions towards Donald Trump and similarities in the emotions of Trump and the audience.

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