Fraud detection in online consumer reviews

Fraud detection in online consumer reviews

Available online 18 August 2010

Opinion Fraud Detection in Online Reviews by Network Effects

User-generated online reviews can play a significant role in the success of retail products, hotels, restaurants, etc. However, review systems are often targeted by opinion spammers who seek to distort the perceived quality of a product by creating fraudulent reviews. We propose a fast and effective framework, FRAUDEAGLE, for spotting fraudsters and fake reviews in online review datasets. Our m...

Marketing Implications of Online Consumer Product Reviews

Modeling Consumer Learning from Online Product Reviews

W propose a structural model to study the effect of online product reviews on consumer purchases of experiential products. Such purchases are characterized by limited repeat purchase behavior of the same product item (such as a book title) but significant past usage experience with other products of the same type (such as books of the same genre). To cope with the uncertainty in quality of the ...

Extracting Product Features from Online Consumer Reviews

The exponential growth of user-generated content in online environment calls for techniques that can help to make sense of the content. Despite of a host of research on online consumer reviews, there is still a great demand for research to improve the techniques for feature extraction. To this end, we proposed extraction methods based on detailed categorization of review features. By taking int...