Impact of COVID-19 on Societal Behavior via Twitter Analytics

• Bhaik, Anubha ^[1] ; Gupta, Pradeep Kumara ^[1] ; Siddiqui, Mohammad Khubeb ^[2] ; Morales-Menendez, Ruben ^[2]
  1. [1] Jaypee University of Information Technology

     Jaypee University of Information Technology

     India

     
  2. [2] School of Engineering and Sciences, Tecnólogico de Monterrey, Monterrey, Mexico.
• Localización: Revista Argentina de Ciencias del Comportamiento ( RACC ), ISSN-e 1852-4206, Vol. 14, Nº. 2, 2022, págs. 37-48
• Idioma: inglés
• DOI: 10.32348/1852.4206.v14.n2.30816
• Títulos paralelos:
  • Impacto del COVID-19 en el Comportamiento Social a través de Twitter Analytics
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    El brote de la pandemia de COVID-19 ha provocado un desafío notable para el bienestar de las personas en todo el mundo. Por lo tanto, es extremadamente importante analizar la información que las personas publican en las redes sociales. Se analizó una base de datos de Twitter relacionada con el COVID-19 y se identificó el efecto de la pandemia en el comportamiento social. Los tweets se han procesado previamente utilizando bibliotecas NLTK para encontrar las palabras relacionadas con COVID publicadas con más frecuencia. Esta investigación puede ayudar a identificar la respuesta social de las personas a la pandemia, reconocer qué es lo que más preocupa y obtener información sobre latendencia diaria en el sentimiento en todo el mundo. Se ha concluido que en lugar de la tendencia negativa esperada en el uso diario de términos COVID19, se ha utilizado un lenguaje figurativo más positivo en los tuits publicados.

  • English

    The outbreak of the COVID – 19 pandemic has caused a notable challenge to the well-being of people all around the globe. In such times, it is of foremost importance to analyze the information posted by people on social media. In this study, a Twitter-based dataset related to COVID-19 has been analyzed, and the effect of the pandemic on societal behavior has been revealed. Tweets have been hydrated and pre-processed using the NLTK toolkit to find the most frequently posted COVID- related words. This research can help identify the social response of people to the Pandemic, realizing what people are majorly concerned about and extracting knowledge about the daily trend of sentiments around the world. It has been concluded from our analysis that rather than the expected negative trend in the use of COVID-19 terms on a daily basis, more positive figurative language has been used in the posted tweets. 

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