surajnakka/graph-data-analysis

Worked with a number of real-world datasets available at http://snap.stanford.edu/ to identify the importance of certain nodes in terms of their degree, betweenness, closeness centralities and clustering co-efficient. • Studied the different random graph generator models to identify the best synthetic random graph generator that reflects real-world datasets better and experimented it with the large social networking sites such as Facebook. • Visualized the graphs using tools such as Gephi, Cystoscape and GraphViz and experimented with different layouts to identify the best visualization layout that distinguishes the critical characteristics of the network.

Python