A heterogeneidade tecnoenunciativa no ecossistema twitter em um conjunto de tuítes reunidos pela hashtag #divulgaçãocientífica

Abstract

Within the scope of Digital Discourse Analysis (DDA), the present study aims to investigate the phenomenon of technoenunciative heterogeneity, in particular reported technodiscourse, and its implications for the action of disseminating science, in scientific dissemination tweets gathered by the hashtag #scientificdissemination. The theoretical contribution is based on DDA studies, especially technoenunciative heterogeneity, focusing on reported technodiscourse, in the light of Paveau (2013; 2014; 2016; 2017; 2021), in the theory of enunciative heterogeneities, via Authier-Revuz (1990; 1998 ; 1999; 2001; 2004; 2008; 2020), Charaudeau (1992, 2008; 2013), Maingueneau (2002; 2014), Brito (2010), Cavalcante et al. (2020) and Pinheiro et al. (2020), and in the postulates about reported speech shared on the Web, according to Grossmann and Rosier (2018) and Grossmann (2019). This investigation comprises description, analysis, and interpretation of a set of five scientific dissemination tweets. This is a qualitative study, supported by the notion of a small corpus, according to Moirand (2020). Through analysis, on Twitter, the category of reported technodiscourse postulated by Paveau (2015; 2017; 2021) is updated, based on the complexity of native digital discourse, allowing a new concept for this object of study through the congruence between Rosier and Grossmann (2018) and Grossmann (2019) and Paveau (2021). Therefore, anchored in the theories of the aforementioned researchers, this research establishes the concept called reported technodiscourse shared on the Web. It is noteworthy, thus, that the theoretical combination carried out in this thesis can offer a more comprehensive overview of the technodiscourse reported category in the Twitter ecosystem, as well as a contribution to Applied Linguistics, the studies of Text, Discourse, and Digital Discourse.