A novel approach to rate and summarize online reviews according to user-specified aspects

As internet use expands, the reviews found on e-commerce websites have greater influence on consumer purchasing decisions. One popular practice of these websites is to provide ratings on predefined aspects of the product, thereby enabling users to obtain summaries of vital information. One limitation of this approach is that rating and summary information is unavailable for aspects of the product that are not predefined by the website. In light of this weakness, this paper proposes a new approach that allows the user to specify the product aspects in which he is interested, whereupon the system automatically classifies and rates all of the online reviews according to those specific aspects. It is worth noting that the proposed method could also assists enterprises to identify the issues of importance to users, which would otherwise be hidden. An understanding of their concerns could be used as a reference in efforts to improve the internal environment and implement service innovations, thereby enhancing customer satisfaction and increasing competitiveness. Analysis of several datasets of hotel reviews made it possible to ascertain the following information for target hotels: (1) the percentages of positive, neutral, and negative comments on various aspects of hotels, as specified by users, (2) average ratings with regard to the aspects specified by users, and (3) categorization of reviews based on specified aspects. Our approach offers the following advantages over current website practices: (1) the functions of our approach are compatible with and can be installed on current e-commerce websites to improve services, (2) users can obtain a summary of information according to their own interests, and (3) our analysis allows users to easily visualize groups of similar opinions.