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.
A Text Mining Analysis on Big Data Extracted from Social Media
Gabriella Schoier
;Giuseppe Borruso;
2020-01-01
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.File in questo prodotto:
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Schoier_A Text Mining Analysis on Big Data Extracted.pdf
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