Modern communication networks are inherently complex in nature. First of all, they have a large number of heterogeneous components. Secondly, their connectivity is extremely dynamic. Nodes can come and go, links can be removed and added over time. Traditional modeling and simulation techniques amalgamate or ignore such dynamics and therefore, are unable to represent them. Complex communication networks are therefore better modeled as mathematical structures called graphs. Modeling as graphs allows for the application of complex techniques such as various network based analysis techniques. While this is a very important and much needed skill for communication networks researchers and engineers, to the best of our knowledge, currently there is no resource describing these details. In this paper, we give a concise but comprehensive review of modeling complex communication networks as graphs. We also show how to apply complex social network analysis on these models besides a demonstration of formal modeling network dynamics.