Turning the Tide: Curbing Deceptive Yelp Behaviors

To catch a fake: Curbing deceptive Yelp ratings and venues

The popularity and influence of reviews, make sites like Yelp ideal targets for malicious behaviors. We present Marco, a novel system that exploits the unique combination of social, spatial and temporal signals gleaned from Yelp, to detect venues whose ratings are impacted by fraudulent reviews. Marco increases the cost and complexity of attacks, by imposing a tradeoff on fraudsters, between th...

What Yelp Fake Review Filter Might Be Doing?

Online reviews have become a valuable resource for decision making. However, its usefulness brings forth a curse ‒ deceptive opinion spam. In recent years, fake review detection has attracted significant attention. However, most review sites still do not publicly filter fake reviews. Yelp is an exception which has been filtering reviews over the past few years. However, Yelp’s algorithm is trad...

Towards a General Rule for Identifying Deceptive Opinion Spam

Consumers’ purchase decisions are increasingly influenced by user-generated online reviews. Accordingly, there has been growing concern about the potential for posting deceptive opinion spam— fictitious reviews that have been deliberately written to sound authentic, to deceive the reader. In this paper, we explore generalized approaches for identifying online deceptive opinion spam based on a n...

Detecting Deception in On and Off-line Communications

As online services become increasingly prevalent, detection of deception in electronic communication becomes vital to maintaining the many communities built around mutual trust between strangers (e.g. OkCupid, Quora, Yelp). Automating the detection process via machine learning has shown promise in recent years. This paper presents the results of using support vector machines (SVMs) and probabil...

Turning the tide against tuberculosis.