Social Network Analysis of Different Parameters Derived From Real-Time Facebook Profiles

With the advent of online social media, it is possible to collect large information and extract information. One of the powerful roles that networks play is to bridge gap between the local and the global perspectives. For example, social network analysis could be used to offer explanations for how simple processes at the level of individual nodes and links can have a global effect. Social networks like Twitter, Facebook, LinkedIn are very large in size with millions of vertices and billions of edges. To collect meaningful information from these densely connected graphs and huge volume of data, it is important to find proper topology of the network as well as conduct analysis based on different network parameters. The main objective of this work is to study the network parameters commonly used to explain social structures. We extract data from the three real-time Facebook accounts using the Netvizz application, analyze and evaluate their network parameters on some widely recognized graph topology using Gephi, a free and open source software.