A Novel Influence Analysis-Based University Major Similarity Study

Ningqi ZHANG, Qingyun LI*, Sissi Xiaoxiao WU, Junjie ZHU, Jie HAN

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review


In the field of education, investigating the relationships between different majors in universities is an important topic in current educational research. The application of social networks from informatics provides new opportunities and potentials for the field of education. Due to the complexity of social interactions, the social network connections surrounding individuals exert a significant influence on their daily decision-making processes. This paper aims to introduce the social network and influence analysis theories from informatics into the field of education, regarding major as a variable, and comparing and analyzing the influence relationships between majors. An empirical study was conducted, involving the collection of questionnaire data on graduates’ evaluations of various aspects of their university experiences across different majors. The evolution of this model follows the DeGroot opinion dynamics with the inclusion of stubborn nodes. By defining leader majors and general majors based on the data and modeling the questionnaire data as the outcome of a discrete random process, an influence matrix is ultimately generated through the opinion dynamic model. Through this modeling approach, we revealed the underlying influence relationships between different disciplines (majors). These findings provide schools with insights to adjust the directions of discipline cultivation, and offer new perspectives and methods for the study of majors in higher education.
Original languageEnglish
Article number337
JournalEducation Sciences
Issue number3
Early online date21 Mar 2024
Publication statusPublished - 21 Mar 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.


  • higher education
  • major similarity
  • data mining
  • influence matrix
  • influence analysis
  • opinion dynamics model
  • social network


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