Describing COVID-19 Pandemic by means of Tweets from Official Entities in Brazil - Santos, Matheus Henrique dos; Pereira, Fabiola S. F. (Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), 2023)
In a world flooded with information, not always true, nor rarely biased, the communication of official entities assumes a key role. In this work we analyze a dataset composed of tweets from stakeholder entities regarding COVID-19 pandemic, to cite: National Agency of Sanitary Surveillance, Ministry of Health, World Health Organization and Brazilian Society of Infectious Diseases. We describe, by means of social, semantic and temporal patterns, the communication characteristics of above entities in social networks during COVID-19 pandemic. Further, we cross those patterns with key-facts occurred during pandemic. Results show that communication in social networks tend to be biased and not sufficient to comprehend the whole context. Furthermore, public entities are immature in their communication strategies in social networks.