Mining product competitiveness by fusing multisource online information

作者:

Highlights:

• Construct a framework by fusing online information to mine product competitiveness

• Design an algorithm to extract product competitiveness information from Q&A

• Apply MI to identify the key competitiveness of product

• Explore the impact of product attributes on key competitiveness

摘要

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

论文关键词:Multisource online information,Product competitiveness,Information fusion,Comparative opinion mining,Quantile regression model

论文评审过程:Received 5 June 2020, Revised 17 December 2020, Accepted 20 December 2020, Available online 23 December 2020, Version of Record 21 February 2021.

论文官网地址:https://doi.org/10.1016/j.dss.2020.113477