Behavioral Analysis of Review Fraud: Linking Malicious Crowdsourcing to Amazon and Beyond

Authors

  • Parisa Kaghazgaran Texas Agricultural and Mechanical University
  • James Caverlee Texas Agricultural and Mechanical University
  • Majid Alfifi Texas Agricultural and Mechanical University

Abstract

We exploit the prevalence of malicious review writers on crowdsourcing platforms like RapidWorkers to identify actual fraud reviews on Amazon. Complementary to previous efforts which often rely on proxies for fraud reviews, we present a long-term study of actual fraudulent behaviors in online review manipulation. We find that these malicious reviewers — though often providing seemingly legitimate opinions — do exhibit significant differences from normal reviewers in terms of ratings distribution, length of the reviews, and the burstiness of the reviews themselves. We additionally study the evolution of these reviews, and find striking temporal changes that could support future discovery of these reviewers who may be “hiding in plain sight.”

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Published

2017-05-03

How to Cite

Kaghazgaran, P., Caverlee, J., & Alfifi, M. (2017). Behavioral Analysis of Review Fraud: Linking Malicious Crowdsourcing to Amazon and Beyond. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 560-563. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14953