Analyzing online groups or the communities in social media networks by algorithmic approach

Abstract

This paper focuses on communities or clusters which are the sets of nodes with lots of links within and very less to the outside of the network. The paper explains the concept of online generation communities and their framework in online social media networks (OSMNs), especially largest networking site, i.e., Facebook. There are many popular methods available for community identification like Walktrap, Nibble, Label Propagation Algorithm (LPA), Fast Community Network Algorithm (FCNA) which had been explored in the last decade. The community framework (CF) is the important and integral part of the OSMNs, but still we have to find the absolutely correct definition of the community in the real-world networks. In this paper, we try to give a correct definition of the community with its few important traits and from that we are able to recommend a different, simple and innovative framework (either flowchart or algorithm) which will resemble the real-world network. In our approach, we try to incorporate or consider those nodes which are overlapped in the community framework with the concept of shortest paths. We believe that our approach will be more favorable than other network methods which mostly generate the partitions.