Analyzing Public Perception of Educational Books via Text Mining of Online Reviews

Abstract

With the development of the era of big data, online reviews have become an important basis for influencing the decisions of consumers, sellers and producers. The research on the publishing of educational books from the perspective of public demand side can provide new ideas for the development of book publishing. This paper explores the public's perception of educational books by text mining reviews of educational books on Douban Books, using a combination of keyword analysis, topic analysis and aspect-level sentiment analysis using tools such as Python. The results indicate that the content quality of educational books strongly influences users' perception. This study reveals the public's perspectives on different aspects of educational books, aiding publishers and authors in gaining deeper insights into areas that require attention and improvement. Based on the analysis results, scientific recommendations are proposed to enhance the quality and publishing standards of educational books, assisting publishers in making publishing decisions that meet the evolving needs of the public. This research contributes to the development of educational book publishing by providing valuable insights and recommendations.