Detecting Fake Reviews

Opinions in social media are increasingly used by individuals and organizations for making purchase decisions and for marketing and product design. Positive opinions can result in significant financial gains and fames for businesses and individuals. This, unfortunately, gives strong incentives for people to game the system by posting fake positive opinions/reviews to some entities (e.g. products and services) in order to promote them, and/or malicious negative reviews to damage their reputations. Such imposters are called opinion spammers and their activities are called opinion spamming. Fake reviews are rampant on the Internet and are seriously undermining the credibility and trustworthiness of online opinions. Fake reviews come from many different sources. Businesses may write for themselves and also pay individuals, middlemen, and also the so-called “reputation management” firms to write on their behalf. They may also ask their customers to write by giving the customers discounts. As more and more individuals and organizations are using reviews for their decision making, detecting fake reviews has become a pressing issue. Many high profile fake review cases have been reported in the news. I have compiled several press articles and interesting links and listed them in my research page (http://www.cs.uic.edu/~liub/FBS/fake-reviews.html). In this talk, I will first introduce the problem and discuss its major challenges. I will then describe some of our recent work on the topic.

Speaker Details

Bing Liu is a professor of Computer Science at the University of Illinois at Chicago (UIC). He received his PhD from the University of Edinburgh. His current research interests include sentiment analysis and opinion mining, opinion spam detection, and social media modeling. He has published numerous papers in leading conferences and journals in these areas, e.g., KDD, ACL, EMNLP, WWW, AAAI, IJCAI, and Computational Linguistics, and has given many invited talks. He also published a book titled “Sentiment Analysis and Opinion Mining” (Morgan and Claypool Publishers). His work on opinion spam (fake review) detection has received a great deal of media attention including a front page article of The New York Times. His earlier research focused on data mining, Web mining, and machine learning, where he also published extensively, including a book titled “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data” (Springer). On professional services, Liu has served as program chairs of KDD, ICDM, WSDM, CIKM, SDM, and PAKDD, and as area/track chairs or senior PC members of many data mining, Web mining, natural language processing, and AI conferences.