Design and Develop a Framework for Social Network Analysis

Abstract

Now a day everything around the globe is connected via networks like information, places and events which make a tangle of connections. The outgrowth and favoritism of online social network made available a large amount of data all of a sudden from social organization, human behavior and their interaction. Analyzing social network is to make sense of these complex connections. This work represents the framework to analyze twitter social media tweets using NetworkX and Twitter API. Python language tool IPython/Jupyter is used to examine the networks by applying visual analytic techniques like degree centrality and betweenness centrality to the dataset of twitter hash tags which provides an easier way to analyze the network connections. This framework describes methodology to diagnose each tweet for identifi cation of certain pattern as `who talk to whom about what'and `most influential person'in the interconnected/attached network.