Open AccessOnline Fraud Review Detection Using Data Mining
Publication year - 2020
Publication title -
international journal for research in engineering application and management
Language(s) - English
Resource type - Journals
ISSN - 2454-9150
DOI - 10.35291/2454-9150.2020.0416
Subject(s) - product (mathematics) , computer science , sentiment analysis , social media , service (business) , internet privacy , data science , world wide web , business , marketing , artificial intelligence , geometry , mathematics
Online reviews have great impact on today’s business and commerce. Decision making for purchase of online products mostly depends on reviews given by the users. Nowadays, there are a number of people using social media opinions to create their call on shopping for product or service. Opinion Spam detection is an exhausting and hard problem as there are many faux or fake reviews that have been created by organizations or by the people for various purposes. They write fake reviews to mislead readers or automated detection system by promoting or demoting target products to promote them or to degrade their reputations, opportunistic individuals or groups try to manipulate product reviews for their own interests. This paper introduces some semi-supervised and supervised text mining models to detect fake online reviews as well as compares the efficiency of both techniques on dataset containing hotel reviews.