Calculating Average Clustering Coefficient for Complex Networks
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Resource Overview
A MATLAB-based tool designed to compute the average clustering coefficient in complex networks, featuring algorithmic implementation and network analysis capabilities.
Detailed Documentation
This tool is developed using MATLAB and primarily serves to calculate the average clustering coefficient of complex networks. The clustering coefficient measures the ratio of connections between any two nodes and their shared neighboring nodes, quantifying the network's clustering density. The implementation utilizes adjacency matrix operations and neighbor node traversal algorithms to efficiently compute local clustering coefficients, which are then averaged across all nodes. This tool assists users in comprehensively understanding and analyzing complex network structures, providing robust support for research in related fields such as social network analysis, biological systems modeling, and infrastructure resilience studies. Key functions include network data preprocessing, degree calculation, and optimized coefficient computation using vectorized operations for improved performance.
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