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A Text Mining Analysis on Big Data Extracted from Social Media

Gabriella Schoier
•
Giuseppe Borruso
•
Pietro Tossut
2020
  • book part

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.
DOI
10.1007/978-3-030-58811-3_25
WOS
WOS:000722380600025
Archivio
http://hdl.handle.net/11368/2976802
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85092237799
https://link.springer.com/chapter/10.1007/978-3-030-58811-3_25
Diritti
closed access
FVG url
https://arts.units.it/request-item?handle=11368/2976802
Soggetti
  • Text Mining

  • Sentiment analysi

  • Big data

  • SARS

  • Coronaviru

Scopus© citazioni
0
Data di acquisizione
Jun 14, 2022
Vedi dettagli
Web of Science© citazioni
0
Data di acquisizione
Mar 26, 2024
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