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