Web Objects Opinion through Sentiment Engineering
Shrinivas Biradar1, G. T. Raju2
1Shrinivas Biradar, Assistant Professor, Department of CSE, RNS Institute of Technology, Bengaluru (Karnataka), India.
2Dr. G. T. Raju, Vice-Principal and Head, Department of CSE, RNS Institute of Technology, Bengaluru (Karnataka), India.
Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 473-476 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11221292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1119.1292S19
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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: Sentiment Analysis is the analysis of thoughts, feelings and qualities of people towards an object. Automatically recognizing user-generated content views is of great help for commercial and political use. Sentiment Analysis / Opinion Mining lets us gather information about the positive and negative characteristics of any given object / product, and we recommend the favorable and highly scoring views on the object / product to the user. Although researchers have contributed a lot towards objects review through sentiment analysis, still there are open issues needs to be addressed such as Negation Handling, Domain Generalization and Detection and Removal of Fake Reviews. This paper presents a review on the various algorithms used for Negation Handling, Domain Generalization and Detection and Removal of Fake Reviews along with a comparative study against performance metrics along with their limitations.
Keywords: Domain Generalization, Fake Reviews, Negation Handling and Sentiment Analysis.
Scope of the Article: Web Technologies