Helpfulness Prediction of Online Product Reviews

The simple question "Was this review helpful to you?" increases an estimated $2.7B revenue to Amazon.com annually (1). In this paper, we propose a solution to the problem of electronic product review accumulation using helpfulness prediction. The popularity of e-commerce and online retailers such as Amazon, eBay, Yelp, and TripAdvisor are largely relying on the presence of product reviews to attract more customers. The major issue for the user submitted reviews is to quantify and evaluate the actual effectiveness by combining all the reviews under a particular product. With the varying size of reviews for each product, it is quite cumbersome for the customers to get hold of the overall helpfulness. Therefore, we propose a feature extraction technique that can quantify and measure helpfulness for each product based on user submitted reviews.