Reviews Analysis of Online Retail Stores in UAE: Analytical Study of Sentiments Through social media
Riktesh Srivastava1, Mohd. Abu Faiz2
1Riktesh Srivastava, Department of Business, Skyline University College, Sharjah UAE.
2Mohd Abu Faiz, Department of Business Management HRM, City University College, Ajman UAE.
Manuscript received on 05 February 2019 | Revised Manuscript received on 13 February 2019 | Manuscript published on 28 February 2019 | PP: 88-92 | Volume-8 Issue-4, February 2019 | Retrieval Number: D2651028419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Text mining for social media has now become decisive tool for marketing, and many businesses understand the supremacy of embracing technology into their marketing campaigns. These texts are the “Consumer language”, owing to its spread and reach. There is no reservation that use of user generated texts has stimulated the companies to identify them and use it for decision making, however, classifying sentiment analysis through these texts is still a fresh sensation. Online retail companies in UAE are an early adopter of social media, but how do they use text mining techniques is still a matter to wary upon. The study proposes a model to collect reviews from multiple sources and identify sentiments and topics simultaneously. The model is the tested on 3 online retail companies in UAE and the results depicts productive outcomes.
Keyword: Sentiment Analysis, Liu Hu Algorithm, Plutchik Modeling, Latent Semantic Indexing.
Scope of the Article: Social Networks