Opinion Mining and Improvised Algorithm for Feature Reduction in Sentiment Analysis
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 4
Abstract
Nowadays organisations use the power of the web to analyse the review of the product by customer. The organisation cannot trust star based reviews because it can be faked by robots. That is why textual review is preferable. Opinion mining is used to find the approximate sentiment of the review. Sentiment analysis is a part of opinion mining which helps an organisation to get valuable feedback of the product by extracting the polarity of reviews. The review of a product may be used to improve productivity of the organisation as it could improve its product's features based on reviews. It provides us ways to analyse a given review. In our review paper, we have emphasised on the content based analysis of the review rather than deciding the contextual polarity by its topic. We have reached to our proposed algorithm by referring to BoPang and LillianLee’ s [2] paper and Tirath Prasad Sahu and Sanjeev Ahuja’ s [3] paper.
Authors and Affiliations
Siddharth. J, Ashish . S, Shreyash . A, Rishi . A, Prashant . U
Keywords
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- EP ID EP390928
- DOI 10.9790/9622-0704021419.
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