Uma análise dos atos de fala ilocucionários expressivos no caso de Kathlen Romeu nos comentários do Twitter

Abstract

Language is an important means of communication for human beings. On Twitter, people use this space to disseminate thoughts, information, and to express ideas and feelings. In this communicative process, speakers perform expressive illocutionary speech acts and hate speech, with different purposes and intentions. To understand them, we developed a basic and descriptive research, with qualitative data analysis. We believe that this research can contribute to scientific knowledge by reducing the gaps in the number of investigations about expressive illocutionary acts and hate speech in online interactions, especially in situations of racism. To this end, we guided our studies on the research of Serhan and Elareshi (2018), Gelashvili (2018), Piscesco (2022), and Ferdiansa (2022). The setting of our investigation was the case of Kathlen Romeu, a black woman who was pregnant when she was hit by a stray bullet in Rio de Janeiro in June 2021. This crime triggered social and virtual manifestations indexed by #justicaporkathlenromeu. Given this, we listed the following questions: What are the types of expressive illocutionary acts found in #justicaporkathlenromeu, in Twitter comments? How are hate speeches found classified? And what are the expressive forms of these speeches? From that, the general objective is to identify the typology of expressive illocutionary speech acts and to classify the hate speeches and its forms of manifestation in Twitter comments, in the hashtag mentioned above. We searched for a theoretical basis in the Pragmatics approach with Yule (2022), dialoguing with the speech act theories of Austin (2020), Searle (2002), Searle and Vandeverken (2009), and Butler (2021). As for the methodology, we conducted virtual field research, in the period from 08.06.2021 to 10.06.2021, with non-participant observation and digital Ethnography (Hine, 2020; McGranahan, 2019). From the 500 comments collected, we reduced the corpus to 269 tweets, following Miles et al's (2014) interactive model. The results showed that the most found expressive illocutionary speech acts were: 60 (29.85%) complaints, 41 (20.39%) protests, and 54 (26.86%) lamentations. In hate speech, the most recurrent were those with racist content in the forms of 09 (13.23%) incitements, 14 (20.58%) provocations, and 25 (36.76%) insults. In the context of our investigation, we found that interlocutors through their speech can potentiate violence and hate speech through different language acts using social media as a tool.