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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Social media sentiment analysis for business analytics |
| Authors Name: | ATHIRA R S , DR. A JAMMER BHASHA |
| Unique Id: | IJSDR1905056 |
| Published In: | Volume 4 Issue 5, May-2019 |
| Abstract: | Social media plays a vital role in generating valuable data as a data source for obtaining inferences and building strategies for business marketing. The vast amount of data produced every day in social media platforms are treasures for data analytics as they can be wisely used to understand the attitude of people regarding specific products. Sentiment analysis performed on these data provides valuable business insights. Organizations tends to use more social media for getting insight into consumer behavioral tendencies, market intelligence and present an opportunity to learn about customer review and perceptions. Applications like Twitter, Yelp and Amazon offers organizations a fast and effective way to analyze customers’ perspectives toward the critical to success in the market place. Building a system for sentiment analysis is an approach to be used to computationally measure customers’ perceptions. This paper reports on the design of a sentiment analysis app by extracting a vast amount of tweets, fetching user reviews from amazon and yelp. An e-commerce prototype is also used for customer behavior prediction. Fake reviews are detected using machine learning techniques. Results classify customers’ perspective via tweets into positive and negative, which is represented in a pie chart, histogram, data tables and html page. Reviews are analyzed and categorized into fake reviews and real reviews |
| Keywords: | Social media analysis, Sentiment analysis, Business analytics, fake review detection, Amazon review analysis, Twitter sentiment analysis |
| Cite Article: | "Social media sentiment analysis for business analytics", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 5, page no.319 - 325, May-2019, Available :http://www.ijsdr.org/papers/IJSDR1905056.pdf |
| Downloads: | 000337070 |
| Publication Details: | Published Paper ID: IJSDR1905056 Registration ID:190549 Published In: Volume 4 Issue 5, May-2019 DOI (Digital Object Identifier): Page No: 319 - 325 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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