Visual Analysis of a Co-authorship Network and Its Underlying Structure

An interesting property of network is that the information is not only contained in the entities, but also in the links between them. As the structure of the co-authorship network can greatly influence its function and reflect how the internal information is exchanged. We attempt to get deep insight of the features in a co-authorship network at a university. This is done by the following two steps. First, we will explore the basic statistical properties of the co-authorship network and try to present these properties by different graph drawing techniques. Second, to gain more insight of the co-authorship network, we will use a community detecting algorithm to find the clusters of the network. By filtering the unstable links and detecting the clusters, we find there are many stable links in these clusters and many unstable links take the role of "bridges"\´ between these clusters. By labeling these communities with different department names, we can get an overview of the main research fields of the university and their relations.