 Sentiment Analysis and Opinion Mining (Business Intelligence 1)Amy Van Looy
Chapter 7 in Social Media Management, 2016, pp 133-147 from Springer Abstract: Abstract This chapter covers the first part of our business intelligence discussion and gives the reader insight into opinion mining and sentiment analysis. Social media are seen as big data in the sense that they provide a massive amount of online reviews and ratings that can be collected and analyzed in order to consider the impact these data may have on organizations. Particularly, several studies have shown that more positive reviews and higher rates for an organization (and its products or services) may lead to a significantly higher number of desired business actions (e.g., higher sales or more subscriptions to an online newsletter, etc.). This chapter explains characteristics such as subjectivity and tone in opinions and shows how a sentiment model can be built. The chapter concludes with challenges faced by this research field today. Keywords: Business intelligence; Big data; Opinion mining; Text mining; Sentiment analysis; Content analysis; Reviews; Ratings; Subjectivity; Tone; Polarity; Sentiment words; Sentiment model; Opinion spammingspamming; Monitoring (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-319-21990-5_7 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-21990-5_7 Access Statistics for this chapter More chapters in Springer Texts in Business and Economics from Springer |
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