SPR2EP: A Semi-Supervised Spam Review Detection Framework

Yilmaz C. M., Durahim A. O.

IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, Spain, 28 - 31 August 2018, pp.306-313 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Barcelona
  • Country: Spain
  • Page Numbers: pp.306-313
  • Keywords: Review Spam Detection, Feature Learning, Document and Node Embeddings, Web mining
  • Middle East Technical University Affiliated: Yes


Authenticity and reliability of the information spread over the cyberspace is becoming increasingly important. This is especially important in e-commerce since potential customers check reviews and customer feedbacks online before making a purchasing decision. Although this information is easily accessible through related websites, lack of verification of the authenticity of these reviews raises concerns about their reliability. Besides, fraudulent users disseminate misinformation to deceive people into acting against their interest. So, detection of fake and unreliable reviews is a crucial problem that must be addressed by the security researchers.