Opinion Mining on Amazon Product Data using Dictionary Approach
Jawahar Gawade1, Latha Parthiban2

1Jawahar Gawade, Ph.D Scholar, Department of Computer Science and Engineering, Bharat University, (Tamil Nadu), India.
2Latha Parthiban, Department of Computer Science, Pondicherry University CC, India.
Manuscript received on 12 February 2019 | Revised Manuscript received on 02 March 2019 | Manuscript Published on 08 June 2019 | PP: 65-69 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10130275S419/19©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: In opinion mining, the expression is composed in a normal speech about a topic and classify them as good bad or unbiased based on the human’s view, feeling, thoughts stated in it. Currently, customer views and remarks on goods are multiplying everyday. These remarks are beneficial for different buyers. Human calculation of huge count of reviews is almost not feasible. To interpret this problem an automatic way of a tool to mine the general views of reviewers is required. This paper concentrate on the dictionary based opinion mining of product reviews.
Keywords: Sentiment Analysis, Opinion Mining, Machine Learning, Product Reviews, Semantic Orientation, SentiWordNet.
Scope of the Article: Data Mining