Flow approaches to community detection in complex network systems

Abstract

The paper investigates the problem of finding communities in complex network systems, the detection of which allows a better understanding of the laws of their functioning. To solve this problem, two approaches are proposed based on the use of flows characteristics of complex network. The first of these approaches consists in calculating the parameters of influence of separate subsystems of the network system, distinguished by the principles of ordering or subordination, and the second, in using the concept of its flow core. Based on the proposed approaches, reliable criteria for finding communities have been formulated and efficient algorithms for their detection in complex network systems have been developed. It is shown that the proposed approaches make it possible to single out communities in cases in which the existing numerical and visual methods turn out to be disabled.