Abstract
The novel coronavirus (COVID-19 or SARS-CoV-2) virus spread rapidly, both as a pandemic and as a viral topic of conversation. Social networks, especially after the boom of smartphones, completely revolutionised the speed and channels where information spreads. A clear example of this is how fast information spreads across Twitter, a platform famous for creating trends and spreading the news. This work focuses on the analysis of the overall opinion of the COVID-19 pandemic on Twitter. We attempted to study the polarity and emotional impression of the people applying a series of natural language processing techniques to a total of 270,000 tweets identified as related to COVID-19.
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Llano, J.L., Ceballos, H.G., Cantú, F.J. (2021). How Is Twitter Talking About COVID-19?. In: Stahlbock, R., Weiss, G.M., Abou-Nasr, M., Yang, CY., Arabnia, H.R., Deligiannidis, L. (eds) Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-71704-9_7
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