Community Detection in Social Network with Outlier Recognition

Exploring communities and outliers in Social Network is based on considering of some nodes have overlapped neighbor node within the same group as well as some nodes have no any link to the other node or have no any overlapped value. The existing approaches are based on the overlapping community detection method were only defined the overlap nodes or group of overlap nodes without thinking of which nodes might have individual communities or which nodes are outliers. Detecting communities can be used the similarity measure based on neighborhood overlapping of nodes and identified nodes so called outliers which cannot be grouped into any of the communities. This paper proposed method to detect communities and outliers from Edge Structure with neighborhood overlap by using nodes similarity. The result implies the best quality with modularity measurement which leads to more accurate communities as well as improved their density after removing outliers in the network structure