Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/46378

TitleSentiment analysis with Text Mining in contexts of Big Data
Author(s)Andrade, Carina Sofia Marinho
Santos, Maribel Yasmina
KeywordsBig Data
Internet
No SQL
Sentiment Analysis
Text Mining
Issue date2017
PublisherIGI Global
JournalInternational Journal of Technology and Human Interaction
CitationAndrade, Carina and Maribel Yasmina Santos, "Sentiment Analysis with Text Mining in Contexts of Big Data", International Journal of Technology and Human Interaction, Special Issue on Trends in Information Systems, 13(3), 47-67, July-September, 2017 ISSN: 1548-3908, DOI: 10.4018/IJTHI.2017070104
Abstract(s)The evolution of technology, along with the common use of different devices connected to the Internet, provides a vast growth in the volume and variety of data that are daily generated at high velocity, phenomenon commonly denominated as Big Data. Related with this, several Text Mining techniques make possible the extraction of useful insights from that data, benefiting the decision-making process across multiple areas, using the information, models, patterns or tendencies that these techniques are able to identify. With Sentiment Analysis, it is possible to understand which sentiments and opinions are implicit in this data. This paper proposes an architecture for Sentiment Analysis that uses data from the Twitter, which is able to collect, store, process and analyse data on a real-time fashion. To demonstrate its utility, practical applications are developed using real world examples where Sentiment Analysis brings benefits when applied. With the presented demonstration case, it is possible to verify the role of each used technology and the techniques adopted for Sentiment Analysis.
TypeArticle
URIhttp://hdl.handle.net/1822/46378
DOI10.4018/IJTHI.2017070104
ISSN1548-3908
e-ISSN1548-3916
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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