Twitter has been one of the main sources of information and discussion during the COVID-19 pandemics. This paper characterizes a set of more than 56 million tweets written in Portuguese and collected over a period of 70 days. Our analysis includes the volume of messages, text of tweets, location of tweets, the main elements of tweets (e.g. hashtags and URLs) and the user profiles, including gender. The analyses showed the most discussed topics in the period were quarantine, hydroxychloroquine, agglomeration and social distance, and that the discussions were centered in political issues (e.g., most common hashtags include “fechadocombolsonaro" and “forabolsonaro").
The debate over the COVID-19 pandemic is constantly trending at online conversations since its beginning in 2019. The discussions in many social media platforms is related not only to health aspects of the disease, but also public policies and non-pharmacological measures to mitigate the spreading of the virus and propose alternative treatments. Divergent opinions regarding these measures are leading to heated discussions and polarization. Particularly in highly politically polarized countries, users tend to be divided in those in-favor or against government policies. In this work we present a computational method to analyze Twitter data and: (i) identify users with a high probability of being bots using only COVID-19 related messages; (ii) quantify the political polarization of the Brazilian general public in the context of the COVID-19 pandemic; (iii) analyze how bots tweet and affect political polarization. We collected over 100 million tweets from 26 April 2020 to 3 January 2021, and observed in general a highly polarized population (with polarization index varying from 0.57 to 0.86), which focuses on very different topics of discussions over the most polarized weeks–but all related to government and health-related events.
No Brasil, licitações públicas devem garantir a transparência e a livre concorrência entre licitantes. No entanto, o monitoramento de irregularidades é complexo por envolver um enorme volume de dados e uma quantidade reduzida de especialistas. Nesse contexto, este trabalho propõe o uso de uma metodologia baseada em conceitos de trilhas de auditagem e redes sociais para criar alertas de fraude em licitações, de forma a auxiliar no combate à corrupção. A caracterização e a análise de uma rede social real, associada a um estudo de caso com uma possível licitação fraudulenta, revelam que a metodologia apresentada consegue identificar licitações suspeitas, em geral, identificadas por mais de uma trilha de auditagem.
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