Now a days everything around the globe is connected via networks like information, places and events which make a tangle of connections. 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 hashtags which provides an easier way to analyze the network connections. This framework describes methodology to diagnose each tweet for identification of certain pattern like 'who talk to whom about what' and 'most influential person' in the interconnected/attached network.
