MATLAB Source Code for Complex Network Clustering Coefficient Calculation

Resource Overview

MATLAB source code implementation for calculating clustering coefficients in complex networks, featuring algorithm optimization and network analysis capabilities

Detailed Documentation

MATLAB source code for calculating clustering coefficients in complex networks. This code enables users to compute clustering coefficients, providing deeper insights into network structure and connectivity patterns. The implementation leverages MATLAB's built-in functions and graph theory algorithms to efficiently process adjacency matrices. Key features include: neighborhood identification for each node, triangle counting methods, and normalized coefficient computation. The code utilizes MATLAB's sparse matrix operations for memory efficiency when handling large-scale networks. This implementation serves as a fundamental tool for analyzing complex network properties and can be extended for various research applications in network science. The modular design allows easy integration with other network analysis functions and supports customization for specific network types.