This study investigates the impact of the customer reviews and the incentives on the product sales at the online retail store. Two customer review factors (i.e. average review ratings and the number of reviews) and two customer incentives factors (i.e. price discounts and special shipping offers) are used for the regression analysis. With the sales ranking data collected from the video game tit...

In this paper, we introduce a new methodology for modeling product aspects from a collection of free-text customer reviews. The proposal relies on a language modeling framework and is domain independent. It combines both a kernelbased model of opinion words and a stochastic translation model between words to approach the aspect model of products. We also present a ranking-based methodology to m...

Customers’ concerns about the potential risks in online transactions hinder the development of e-commerce. Researchers have devoted a lot of effort to looking for a way to alleviate the uncertainty pertaining to these risks. Online customer reviews designed to deliver information in addition to a manufacturer’s product description, have attracted researchers’ attention. In this study, we assume...

In this paper, we delve into opinion mining and sentiment analysis of customer reviews posted on online e–Commerce portals such as Amazon.com. Specifically, we look at novel ways of automatic labelling of data for customer reviews by looking at the number of helpful votes and subsequently determine hidden factors that can explain why a customer review is more helpful or trustworthy in contrast ...