Hypothesis Testing for Automated Community Detection in Networks

Understand

Community detection in networks is a key exploratory tool with applications in a diverse set of areas, ranging from finding communities in social and biological networks to identifying link farms in the World Wide Web.

• The problem of finding communities or clusters in a network has received much attention from statistics, physics and computer science.
• However, most clustering algorithms assume knowledge of the number of clusters k.
• In this paper we propose to automatically determine k in a graph generated from a Stochastic Blockmodel.