Determining Customer-Focused Product Features through Social Network Analysis

Customer reviews (CR) is an emerging source to obtain customer requirements about product features. Due to customers’ different preferences, identification of shared interests become important to maximize the overall satisfaction among the target group. This paper aims to provide a feature-based importance rating framework to extract, classify and analyze product features based on online CR data. The framework integrates multiple machine learning and artificial intelligence techniques, which enable CR data to be analyzed in large scale. Besides, social network analysis functions to rate the demand intensity and centrality of product features. An experimental case is conducted to showcase the applicability of the proposed framework.