Abstract:
Community structure in scientific collaboration
network has become an important research area. Coauthor of a paper can be thought of as a collaborative
document between more than one authors. Community
detection in co-authorship network reveals characteristic
patterns of scientific collaboration in computer science
research and help to understand the identity-organization
of the author community. Louvain algorithm is a simple,
easy to implement and efficient to recognize community in
huge networks. In this paper, it is used to examine the
structure of community in Computer University’s coauthor
network in Myanmar. Neo4j is also used to visualize the coauthorship network analysis results. Modularity is used to
measure the quality of the cluster structure found by
community discovery algorithms. In experiment, Louvain
algorithm gives more effective qualitative community
structures than other algorithms in co-authorship network.
