An Expandable Community Division Method for Network Visualization

Large scale network has the characteristics of large number of nodes and complex structure, which makes it difficult to display in limited space. The paper proposes an expandable community division method for network visualization. The method use community detection algorithm based on network modularity to detect the network node and greedy algorithm to find the maximum modularity community. Different community level could hierarchical layout by improved Force-Directed Algorithm, which enables the overall structure and the local detail to display together. Compared with CNM and other community algorithm, this method has high accuracy and efficiency. The experimental analysis shows that the method has notable effect on the display of the large scale network structure.