Detection of review spam: A survey

• We have extracted all types of data that can be used in spam detection techniques.
• We have reviewed state of the art literature in the area of detection of spam reviews.
• In this research, we have categorized and classified spam detection methods and techniques.
• We have provided the strength and weaknesses for these methods and techniques.

In recent years, online reviews have become the most important resource of customers’ opinions. These reviews are used increasingly by individuals and organizations to make purchase and business decisions. Unfortunately, driven by the desire for profit or publicity, fraudsters have produced deceptive (spam) reviews. The fraudsters’ activities mislead potential customers and organizations reshaping their businesses and prevent opinion-mining techniques from reaching accurate conclusions. The present research focuses on systematically analyzing and categorizing models that detect review spam. Next, the study proceeds to assess them in terms of accuracy and results. We find that studies can be categorized into three groups that focus on methods to detect spam reviews, individual spammers and group spam. Different detection techniques have different strengths and weaknesses and thus favor different detection contexts.