Abstract
Taking into account the popularity of sites like Yelp, TripAdvisor or Foursquare- posting online reviews is a very popular way to share opinion on social media websites. 90% of consumer reviews do have an influence on the public. But the trustworthiness of these reviews is still an open issue. The existing researches have focused on the sentiment analysis to detect spam reviews but neglected the personal characteristics of a person posting reviews. This work has focused on spam detection using personal characteristics rather than the reviews. Majority of E-commerce sites describe a customer superficially using his ID (name, email ID). But that is not sufficient to identify the uniqueness of a customer. This work has used two additional attributes of the customer to detect spam reviews like his geographical location and the IP address of the device with which he is accessing different resources on Internet. In addition, we have also proposed a content analysis method to attack non-reviews using spam dictionary. Our proposed spam detection system based on four different attributes together separates our approach from the rest of the related work.
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