CovidTrends: Identifying Behaviors during the COVID-19 Pandemic: An Analysis based on Google Trends and News

  • Marcelo Loutfi UNIRIO
  • Marcelo Tibau UNIRIO
  • Sean Wolfgand Matsui Siqueira UNIRIO
  • Bernardo Pereira Nunes Australian National University


This paper presents the identification of people’s behavioral changes during the Covid-19 pandemic period by analyzing the terms searched on Google’s Trend and news. We developed an artifact, called CovidTrends, used the DSR (Design Science Research) epistemological approach, the Design Science Research Methodology (DSRM), and the document analysis method to list infodemic or people’s behavioral trending of interest on Google and correlating them to news within the timeframe in which the terms’ queries peaked. CovidTrends enabled the identification of three main behaviors, which we verified on news reporting in the media. Then, it proves to be appropriate to support data analysis and identify people’s pandemic behavior.

Palavras-chave: Covid-19, Google Trends, Brazil, human behavior


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LOUTFI, Marcelo; TIBAU, Marcelo; SIQUEIRA, Sean Wolfgand Matsui; NUNES, Bernardo Pereira. CovidTrends: Identifying Behaviors during the COVID-19 Pandemic: An Analysis based on Google Trends and News. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 17. , 2021, Uberlândia. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 .

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