Uniting Politics and Pandemic: a Social Network Analysis on the COVID Parliamentary Commission of Inquiry in Brazil - Santos, Lucas Raniére Juvino; Marinho, Leandro Balby; Campelo, Claudio Elizio Calazans (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia), 2022)
Installed in April 2021, the COVID-19 Parliamentary Commission of Inquiry (PCI) aimed to investigate omissions and irregularities committed by the federal government during the COVID pandemic in Brazil, which resulted in the death of more than 660,000 Brazilians and placed it among the countries with the most deaths caused by COVID-19. The investigated government was elected in 2018, in one of the most polarized elections in Brazilian history, and social media played a prominent role in this polarization. Not far from that, the PCI also generated a great popular commotion on social media networks. This paper aims to analyze the public debate related to the PCI of COVID on Twitter, identifying groups, examining their characteristics and interactions, and verifying evidence of political polarization in this social network. For this, we collected 3,397,933 tweets over a period of 26 weeks, and analyzed four distinct networks, based on different types of users interactions, to identify the main actors and verify the presence of segregated groups. In addition, we use natural language preprocessing to detect group characteristics and toxic speech. As a result, we identified three users groups, based on their use of hashtags and using a community detection technique. The group against the PCI is made up of conservatives and supporters of the government targeted by the investigations and presents the highest internal homogeneity. The other two groups, moderated users and opposed to the government, are formed by actors from the most varied political spectrum, containing users from the political left, center, and right, in addition to the main media outlets in the country. Moreover, other evidences of political polarization were found even in less segregated networks, where users from different groups interact with each other, but with the presence of toxic speech.