Newman Fast Community Aggregation Algorithm for MATLAB

The Newman Fast Community Aggregation Algorithm implemented in MATLAB environment serves as an effective tool for social network analysis. This algorithm identifies community structures within networks, enabling better understanding of network organization and functionality. Based on node linkage patterns and modularity optimization concepts, the algorithm partitions network nodes into communities with strong internal connections. The MATLAB implementation typically involves adjacency matrix representation and utilizes hierarchical clustering approaches through iterative merging of node pairs that yield maximum modularity gain. Key functions often include modularity calculation, community merging operations, and dendrogram visualization. By employing Newman's algorithm, researchers can gain deeper insights into social networks, discover node relationships, and obtain valuable perspectives for network enhancement. The code structure usually follows a bottom-up approach where communities are progressively merged while tracking modularity values to determine optimal partitioning.