# Extended Directed Fuzzy Social Network Analysis: A framework and application to curriculum networks in Chinese vocational education

## TL;DR

This paper introduces a new framework for analyzing fuzzy social networks, applied to curriculum networks in Chinese vocational education to identify core courses and highlight differences between majors.

## Contribution

The paper proposes the Extended Directed Fuzzy Social Network Analysis Framework (EFDSNAF) and introduces the Total Fuzzy Intensity of Path (TFIP) for improved network analysis.

## Key findings

- EFDSNAF effectively identifies core courses in vocational education curriculum networks.
- The framework captures essential disciplinary differences between two urban rail transit majors.
- Optimized fuzzy centrality measures demonstrate improved efficacy in analyzing network relationships.

## Abstract

Due to the differences in node types and the diversity of network relationships, Fuzzy Social Network Analysis (FSNA) needs to specifically address the issues of network heterogeneity and relationship ambiguity. To address this challenge, we propose a new analytical framework called Extended Directed Fuzzy Social Network Analysis Framework (EFDSNAF), which establishes the Typical Connections to assist in evaluating the fuzzy network. Meanwhile, in the area of fuzzy centrality measures, we enhance the variability of the Fuzzy Intensity of Path and propose the term “Total Fuzzy Intensity of Path” (TFIP), considering the distinct characteristics of different networks may lead to variations in path intensity expressions and differences in closeness relationships. Based on this, we optimize the computational methods for fuzzy betweenness centrality and fuzzy closeness centrality, with the efficacy of the method being demonstrated through two examples. Then we applied EDFSNAF to analyze Chinese vocational education curriculum network, with empirical investigation on the Urban Rail Transit Operation and Management Major (URTOMM) and Urban Rail Transit Communication and Signaling Technology Major (URTCSTM). Through EDFSNAF, core courses were identified, and network metrics for different majors effectively captured essential disciplinary differences between the two fields, clearly demonstrating the effectiveness of EDFSNAF.