A Book-Influence-Evaluation Method Based on User Ratings of E-Commerce Platform

Abstract

In online social networks, finding high-influence nodes is a crucial component of complex network research. A new book impact evaluation method based on user rating is proposed in this research for the social network created by the buying and selling behaviors on the e-commerce platform. It intends to rank the book nodes in accordance with customer feedback data following user purchases. The method calculates the influence score of a book by predicting its popularity based on user evaluations of the book. To verify the validity and accuracy of the method, the research analyzes a real review dataset from Amazon, a large e-commerce platform, and designs two comparison experiments with different time spans and compares them with five other web analytics metrics. The experimental findings show that the method is efficient and precise in evaluating the influence of book nodes.