Welcome to the InfoSci Platform
Reference Hub4
Sentiment Analysis with Text Mining in Contexts of Big Data

Sentiment Analysis with Text Mining in Contexts of Big Data

Carina Sofia Andrade, Maribel Yasmina Santos
Copyright: © 2017 |Volume: 13 |Issue: 3 |Pages: 21
ISSN: 1548-3908|EISSN: 1548-3916|EISBN13: 9781522511298|DOI: 10.4018/IJTHI.2017070104
Cite Article Cite Article

MLA

Andrade, Carina Sofia, and Maribel Yasmina Santos. "Sentiment Analysis with Text Mining in Contexts of Big Data." IJTHI vol.13, no.3 2017: pp.47-67. http://doi.org/10.4018/IJTHI.2017070104

APA

Andrade, C. S. & Santos, M. Y. (2017). Sentiment Analysis with Text Mining in Contexts of Big Data. International Journal of Technology and Human Interaction (IJTHI), 13(3), 47-67. http://doi.org/10.4018/IJTHI.2017070104

Chicago

Andrade, Carina Sofia, and Maribel Yasmina Santos. "Sentiment Analysis with Text Mining in Contexts of Big Data," International Journal of Technology and Human Interaction (IJTHI) 13, no.3: 47-67. http://doi.org/10.4018/IJTHI.2017070104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.