A Novel Data Analytic Model for Mining User Insurance Demands from Microblogs

Authors

  • Chun Yan College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China & College of Mathematics and System Science, Shandong University of Science and Technology, Qingdao 266590, China
  • Lu Liu College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China
  • Wei Liu College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
  • Man Qi School of Engineering, Technology and Design, Canterbury Christ Church University, CT1 1QU, United Kingdom

DOI:

https://doi.org/10.31577/cai_2022_3_689

Keywords:

LDA model, Word2Vec, insurance demand, preferences

Abstract

This paper proposes a method based on LDA model and Word2Vec for analyzing Microblog users' insurance demands. First of all, we use LDA model to analyze the text data of Microblog user to get their candidate topic. Secondly, we use CBOW model to implement topic word vectorization and use word similarity calculation to expand it. Then we use K-means model to cluster the expanded words and redefine the topic category. Then we use the LDA model to extract the keywords of various insurance information on the “Pingan Insurance” website and analyze the possibility of users with different demands to purchase various types of insurance with the help of word vector similarity. Finally, the validity of the method in this paper is verified against Microblog user information. The experimental results show that the accuracy, recall rate and F1 value of the LDA-CBOW extending method have been proposed compared with that of the traditional LDA model, respectively, which proves the feasibility of this method. The results of this paper will help insurance companies to accurately grasp the preferences of Microblog users, understand the potential insurance needs of users timely, and lay a foundation for personalized recommendation of insurance products.

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Published

2022-09-08

How to Cite

Yan, C., Liu, L., Liu, W., & Qi, M. (2022). A Novel Data Analytic Model for Mining User Insurance Demands from Microblogs. COMPUTING AND INFORMATICS, 41(3), 689–713. https://doi.org/10.31577/cai_2022_3_689

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