Document Type : Primary Research paper
Assistant Professor, Department of CSE, Nehru Institute of Technology
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.