Poster Abstract: Spotting Suspicious Reviews via (Quasi-) clique Extraction. Jain, P., Chen, S., Azimpourkivi, M., Chau, Horng, D., & Carbunar, B. IEEE Security and Privacy, May, 2015.
abstract   bibtex   
How to tell if a review is real or fake? What does the underworld of fraudulent reviewing look like? Detecting suspicious reviews has become a major issue for many online services. We propose the use of a clique-finding approach to discover well-organized suspicious reviewers. From a Yelp dataset with over one million reviews, we construct multiple Reviewer Similarity graphs to link users that have unusually similar behavior: two reviewers are connected in the graph if they have reviewed the same set of venues within a few days. From these graphs, our algorithms extracted many large cliques and quasi-cliques, the largest one containing a striking 11 users who coordinated their review activities in identical ways. Among the detected cliques, a large portion contain Yelp Scouts who are paid by Yelp to review venues in new areas. Our work sheds light on their little-known operation.
@article{ Jain2015,
  abstract = {How to tell if a review is real or fake? What does the underworld of fraudulent reviewing look like? Detecting suspicious reviews has become a major issue for many online services. We propose the use of a clique-finding approach to discover well-organized suspicious reviewers. From a Yelp dataset with over one million reviews, we construct multiple Reviewer Similarity graphs to link users that have unusually similar behavior: two reviewers are connected in the graph if they have reviewed the same set of venues within a few days. From these graphs, our algorithms extracted many large cliques and quasi-cliques, the largest one containing a striking 11 users who coordinated their review activities in identical ways. Among the detected cliques, a large portion contain Yelp Scouts who are paid by Yelp to review venues in new areas. Our work sheds light on their little-known operation.},
  author = {Jain, Paras and Chen, Shang-Tse and Azimpourkivi, Mozhgan and Chau, Duen Horng and Carbunar, Bogdan},
  journal = {IEEE Security and Privacy},
  title = {Poster Abstract: Spotting Suspicious Reviews via (Quasi-) clique Extraction},
  year = {2015},
  month = {May}
}

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