A Study On Online Spam Review Detection Methods By Machine Learning Approach

Main Article Content

Dr.Sudha Rajesh, et. al.

Abstract

Online reviews for products, movies, shopping, etc. have become the major purchase decision of customers to make before buying the product. These reviews are kind of public opinion about the product which they bought and this may help another person who is willing to buy the product. The impact of reviews had made manufacturers, and retailers to be more concerned about making the product as a best one. Many retailers such as Reliance, Big Bazaar, More, etc are very concerned about online reviews and there are possibilities for these reviews to affect business either positively or negatively.  Certain retailers are trying to create false reviews about the product through AI as a part of promoting the product. This process is termed the  Opinion spam or opinion review spam here is where the reviewers manipulate a wrong review for selling the product for profit. Not all online reviews are trustworthy and truthful so in such cases, a model must be created for detecting online review spam. This research paper tries to highlight the online spam review detecting by machine learning approach using NLP (Natural Language Processing) where the extracted features from the text will be taken for further review. In this research main focus was shifted to the ML technique for detecting review spam, and classifying them. The main aim of the research is to provide a comprehensive ad strong ML approach for detecting review spam.

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How to Cite
et. al., D. R. . (2021). A Study On Online Spam Review Detection Methods By Machine Learning Approach. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(9), 1292–1304. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/3482
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