O populismo de Donald Trump: o twitter na construção de uma plataforma política de direita radical (2015-2016)

• Ano de defesa: 2024
• Autor(a) principal: Rabêlo, Rebeca Souza
• Orientador(a): Pacheco, Cristina Carvalho
• Banca de defesa: de Barros, Thomás Zicman , Nobre, Fábio Rodrigo Ferreira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual da Paraíba
• Programa de Pós-Graduação: Programa de Pós-graduação em Relações Internacionais - PPGRI
• Departamento: Centro de Ciências Biológicas e Sociais Aplicadas - CCBSA
• País: BR
• Palavras-chave em Português: Donald Trump; Twitter; Populismo; Segurança ontológica
• Palavras-chave em Inglês: Donald Trump; Twitter; Populism; Ontological security
• Área do conhecimento CNPq: CIENCIA POLITICA
• Link de acesso: https://repositorio.uepb.edu.br/handle/123456789/74451

How Does the Far-Right Use Social Media to Build Its Political Platforms? This work hypothesizes that Donald Trump used his social media profile as a tool to construct a Radical Right-Wing Populist (RRP) political platform by exploiting populist, nativist, and authoritarian narratives. Throughout the United States 2015 presidential elections, Donald Trump adopted digital platforms, especially Twitter, as a direct communication channel with his voters. In the tweets published by Trump at the time, it was possible to identify a narrative that emphasized the United States was undergoing a crisis, mostly associated with anti-immigration, xenophobic, and nativist elements that fueled a sense of insecurity. Trump's emotionally charged tweets fed this need by presenting a worldview in which voters' security was threatened by factors such as immigration, cultural diversity, and social changes. The theoretical framework used in this dissertation refers to Ontological Security, given that Trump's emotionally charged tweets fed this need by presenting a worldview in which voters' security was threatened by factors such as immigration, cultural diversity, and social changes. Through this connection between the crisis narrative and the need for ontological security, Trump's tweets may have played a significant role in shaping voters opinions by capitalizing on perceived fear and insecurity to gain political support, positioning himself as the leader capable of restoring order and protecting traditional values. Regarding the methodology, computational text mining and analysis methods were employed. In the context of this research, Principal Component Analysis (PCA) is used to reduce the dimensionality of the vectorized tweet data, facilitating the application of the K-means clustering algorithm. The tweet analysis is conducted using the Python programming language and Jupyter Notebook to implement the content analysis technique. This approach made it possible to identify elements with populist, authoritarian, and nativist characteristics in Trump's tweets during the campaign.