Mining product competitiveness by fusing multisource online information

Abstract In sharp market competition, it is very important for enterprises to maintain high product competitiveness. The rich data on social network sites and e-commerce platforms provide a novel way to research product competitiveness. Some studies have mined product competitiveness from online reviews, which may be biased, since some fake information may be contained in online reviews, and the information of product competitiveness from the online reviews is limited as well. This paper, thus, proposes a method that integrates multisource online information to analyze product competitiveness, which can correct the deviation of product competitiveness from a single source of online reviews. In addition, this method is based on mutual information and quantile regression models and further explores what the key competitiveness is and how the factors affect product competitiveness at different competitiveness levels. This paper provides a novel decision-making tool to analyze the competitiveness of products such as mobile phones