Detection of Spam Reviews and Spammers in E-Commerce Sites

E-services have grown tremendously in the last ten years, as people prefer online shopping. This is because they no more have time to go to real markets, to bargain with sellers or to negotiate. In recent years, online reviews have become the most significant means of customers' opinions. However, driven by the desire for profit or publicity, fraudsters have produced deceptive (spam) reviews affecting the organization's business. Filtering out this spam reviews ensures trust and credibility among the users. The present research proposes a systematic pproach for detection of spam reviews and spammers using a fuzzy based approach. Along with review text mining, customer loyalty based on purchasing behavior is considered as input to the fuzzy inference system. After filtration of spam reviews and spammers based on spam degree assigned to the reviews the new overall score for the product is calculated.