Analysis of Variation of Discourse Cohesion About COVID-19 in Social Media

• João Matheus N. Gonçalves Federal University of Rio de Janeiro (UFRJ)
• Jonice Oliveira Federal University of Rio de Janeiro (UFRJ) http://orcid.org/0000-0002-2495-1463
• Fabio Porto National Laboratory for Scientific Computing (LNCC)
• Tiago C. França Federal Rural University of Rio de Janeiro (UFRRJ)

DOI: https://doi.org/10.5753/sbbd_estendido.2023.235175

Abstract

During the course of extreme events, such as the COVID-19 pandemic, a large volume of publications on the topic tends to occur on social media. The public reports and shares opinions about the event and its sub-events, leading to a variation of the discourse over time, which requires computational solutions for its analysis, mainly due to the volume of data and duration of the analyzed period. In this work, we apply the VERSATILE method, for the analysis of textual cohesion over time, in a database with a large volume of tweets in Portuguese published in the first semester of the pandemic. It was possible to correlate variations in textual cohesion with sub-events related to COVID-19 in Brazil and around the world, in addition to better understanding the metrics used for the analysis.

Keywords: COVID-19, extreme events, social network analysis, natural language processing

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