Variable Clustering Scale-Free Network
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Resource Overview
Source code for variable clustering scale-free networks, enhancing BA network's clustering coefficient through adaptive clustering mechanisms.
Detailed Documentation
This variable clustering scale-free network source code implements an algorithm designed to enhance the clustering coefficient of Barabási-Albert (BA) networks. The algorithm incorporates an adaptive clustering mechanism that enables nodes to form additional cluster structures, thereby increasing the overall clustering coefficient of the network.
Key implementation features include:
- Dynamic edge rewiring based on local connectivity patterns
- Priority attachment considering both node degree and triangular closure
- Tunable parameters for controlling clustering intensity
This enhanced algorithm proves valuable in practical applications such as social network analysis, information diffusion modeling, and complex network simulations where higher clustering coefficients better reflect real-world network characteristics.
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