Assistant Professor, Department of CSE, Nehru Institute of Technology
Abstract
Online reviews have a huge impact on the customer’s choice for purchase. These reviews are being read and affects a lot of user decision whether to buy a product or not. There are a lot of reviews based on a product majority of which turns out to be fake written by people to defame a product, which is often created by the competitors of a particular product. The present research concentrates on spam detection and categorizing them from these reviews. We have found that the studies can be classified into three groups that focus on methods to detect fake reviews, individual spammers and group fraudsters. Different techniques have been used for the detection of fake reviews, and block them. In this study a novel framework to improve Netspam method is proposed. The reviews are analysed by the admin and if found spam, the user is blocked from access his account. The results shows that it is more efficient in preventing people from creating fake reviews, whereas existing methods defines which is a fake review and which is not.
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