From Opinion Mining to Improvement Mining : Understanding Product Improvements from User Reviews

A valuable trove of information exists for product(s) or services online via user opinions like detailed reviews provided by customers on popular e-commerce websites. Users express their individual opinions in the form of overall product/service experiences, which may include explicit positive/negative feedback, preferences, concerns, and suggestions for the future. Such information can be valuable to product/service owners in helping them understand the improvement(s) that must be made to a particular product or service. The primary focus of opinion mining has been on understanding positive and negative aspects within the review effectively. Limited emphasis has been placed on finer topics like user suggestions or conflicting information from users. In this work, we describe a method to extract possible product / service improvements from opinionated text in the form of non-conflicting negative feedback, user tips, recommendations, product usage details, feature suggestions, and specific complaints.