Categorizing Quality Determinants in Mining User-Generated Contents

Abstract

User-Generated Contents (UGCs) are gaining increasing popularity as a source of valuable information for companies to manage the quality of their products, services and Product-Service Systems (PSS). This paper aims at proposing a novel approach to identify and categorize quality determinants through the analysis of an extensive database of UGCs. In detail, this paper applies a topic modeling algorithm (Structural Topic Model) to identify quality determinants and introduces the Mean Rating Proportion measurement for their classification into three categories: negative, positive and neutral quality determinants. The application of the proposed methodology is exemplified through the analysis of a PSS case study (car-sharing).