Relacionando Modelagem de Tópicos e Classificação de Sentimentos para Análise de Mensagens do Twitter Durante a Pandemia da COVID-19

  • Matheus Adler Soares Pinto UEMA
  • Antonio Fernando Lavareda Jacob Junior UEMA
  • Antonio José G. Busson PUC-Rio
  • Sérgio Colcher PUC-Rio

Resumo


In 2020, COVID-19 pandemic is one of the most talked-about subjects on social networks. This subject has generated discussions of great importance about politics, economics, medical advances, people’s awareness, preventive techniques, etc. Using sentiment analysis and topic modeling techniques, in this paper, we aim to present an analysis of the messages from the social network Twitter during the pandemic of COVID-19. For this, we use a tweets dataset to train a sentiment classifier and then use the NMF algorithm to perform the interest topic generation.

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Publicado
30/11/2020
PINTO, Matheus Adler Soares; JACOB JUNIOR, Antonio Fernando Lavareda ; BUSSON, Antonio José G.; COLCHER, Sérgio. Relacionando Modelagem de Tópicos e Classificação de Sentimentos para Análise de Mensagens do Twitter Durante a Pandemia da COVID-19. In: WORKSHOP DE TRABALHOS DE INICIAÇÃO CIENTÍFICA - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 26. , 2020, São Luís. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 61-64. ISSN 2596-1683. DOI: https://doi.org/10.5753/webmedia_estendido.2020.13064.