The Analysis of Sub-Communities Behavior in Social Networks

Abstract

Clique relations are useful in understanding the dynamics of a wide range of social interactions. One application of studying clique relations involves studying how such “detection of abnormal cliques’ behaviors” can be used to detect sub-communities’ behaviors based on information from Online Social Networks (OSNs).In social networks, a clique represents a sub-group of the larger group in which every member in the clique is directly associated with every other member in the clique. Those cliques often possess a containment relation with each other where large cliques can contain small size cliques. Thus, finding the extent of the clique, or the maximum clique is an important research questions. In our approach, we evaluated adding the weight factor and integrating graph theory to clique algorithm in order to derive more data about the clique. In this regard clique activities are not like those in group discussions where an activity is posted by one user and is visible by all others. Our algorithm calculates the overall weight of the clique based on individual edges. Users post frequent activities. Their clique members, just like other entities, may or may not interact with all those activities.