Perspective on Measurement Metrics for Community Detection Algorithms

Community detection or cluster detection in networks is often at the core of mining network data. Whereas the problem is well-studied, given the scale and complexity of modern day social networks, detecting “reasonable” communities is often a hard problem. Since the first use of k-means algorithm in 1960s, many community detection algorithms have been presented—most of which are developed with specific goals in mind and the idea of detecting meaningful communities varies widely from one algorithm to another.