Discovery and Visualization of Hierarchical Overlapping Communities from Bibliography Information

A bibliographic database houses vital information pertinent to the research community. By extracting implicit hidden information in such data collections, social networks can be used to represent the various data inter-relationships.In this paper, we propose a new method for the discovery and visualization of research communities from bibliography information. We utilize the hierarchical overlapping communities (HOC) algorithm to identify the hierarchical overlapping communities based on the common neighborhood, and e-spring algorithm to visualize the derived communities.This method has been validated by visualizing synthetic datasets, and research communities obtained from the DBLP bibliography data.