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The COVID-19 outbreak: social media sentiment analysis of public reactions with a multidimensional perspective

Coronavirus pandemic has driven the entire world to crush. It has influenced every single segment of society straightforwardly and in a roundabout way. There is an unexpected break in everything. A monetary downturn, psychological maladjustment, and joblessness are spreading its underlying foundatio...

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Detalles Bibliográficos
Autores principales: Agarwal, Basant, Sharma, Vaishnavi, Harjule, Priyanka, Tiwari, Vinita, Sharma, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9261777/
http://dx.doi.org/10.1016/B978-0-12-824557-6.00013-3
Descripción
Sumario:Coronavirus pandemic has driven the entire world to crush. It has influenced every single segment of society straightforwardly and in a roundabout way. There is an unexpected break in everything. A monetary downturn, psychological maladjustment, and joblessness are spreading its underlying foundations alongside the spread of COVID-19. To forestall the spread of COVID-19, the Indian government has made different strides. One such measure was the whole country lockdown, which was put in place on March 22, 2020. Despite the fact that the countrywide lockdown was implemented to curtail the spread of infection, numerous issues have risen alongside the lockdown. In this chapter, we compare the impact of COVID-19 on the five worst-hit countries in the world. Further, temporal sentiment analysis of Twitter data to understand the effect of lockdown on public perception in these five countries is presented. Results reveal that sentiments in the United States vary from neutral to negative, whereas, in India and Italy, people have mixed attitudes toward the 2019-nCOV-2 virus crises. Further, the impact of government control policies through various stages of lockdown in India is analyzed, which provides interesting aspects of public emotions. Some of the most trending hashtags such as #WorkFromHome and #MigrantLabour are also analyzed using sentiment analysis techniques. It was observed that most people had positive sentiments about working from home during the lockdown. At the same time, migrant workers’ stories dominated on Twitter.