Abstract
The aim of this paper is to analyze data derived from Social Media. In our time people and devices constantly generate data. The network is generating location and other data that keeps services running and ready to use in every moment. This rapid development in the availability and access to data has induced the need for better analysis techniques to understand the various phenomena. We consider a Text Mining and a Sentiment Analysis of data extracted from Social Networks. The application regards a Text Mining Analysis and a Sentiment Analysis on Twitter, in particular on tweets regarding Coronavirus and SARS.
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CITATION STYLE
Schoier, G., Borruso, G., & Tossut, P. (2020). A Text Mining Analysis on Big Data Extracted from Social Media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12252 LNCS, pp. 351–364). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58811-3_25
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