Designing novel review ranking systems: predicting the usefulness and impact of reviews

With the rapid growth of the Internet, users' ability to publish content has created active electronic communities that provide a wealth of product information. Consumers naturally gravitate to reading reviews in order to decide whether to buy a product. However, the high volume of reviews that are typically published for a single product makes it harder for individuals to locate the best reviews and understand the true underlying quality of a product based on the reviews. Similarly, the manufacturer of a product needs to identify the reviews that influence the customer base, and examine the content of these reviews. In this paper, we propose two ranking mechanisms for ranking product reviews: a consumer-oriented ranking mechanism ranks the reviews according to their expected helpfulness, and a manufactureroriented ranking mechanism ranks the reviews according to their expected effect on sales. Our ranking mechanism combines econometric analysis with text mining techniques in gen...

• Type: Conference
• Year: 2007
• Where: ACMICEC
• Authors: Anindya Ghose, Panagiotis G. Ipeirotis
• Keywords: ACMICEC 2007, ECommerce, Product Review, Ranking Mechanism, Review