COVID-19 and the circulation information on social networks: analysis in a Brazilian Facebook group about the Coronavirus - Cordeiro, Douglas Farias; Rocha, Anelise Souza; Machado Vieira, Larissa; Cassiano, Kátia Kelvis; Da Silva, Núbia Rosa (Em Questão, 2021)
This article aims to quantify and qualify the information circulating in social media groups about COVID-19, the subjects covered in posts, as well as the possible relations with other subjects, events or social events, in order to generate a representative panorama of perception and social reaction to the coronavirus pandemic. For this, statistical techniques, data mining and machine learning are used to the characterization, pattern detection, and grouping of textual data. The experiments are carried out on a dataset of textual data extracted from a Brazilian public group about COVID-19 (SARS-cov-2) of the social network Facebook. Statistical analyzes are crossed with data on the advance of the number of infected, and with specific political-social events, revealing variations and influences in terms of participation and engagement in the analyzed group. In addition, through the results obtained by the clustering method used, two main groups of posts are detected, the first presenting a content pattern geared to governmental issues, and the second to personal issues. The results achieved still allow a reflection on the possible social impacts of the creation or absence of public policies to deal with the COVID-19 pandemic.