About scale-free networks

Nowadays I am working on scale-free networks and community structure identification in these networks. These networks are quite interesting because of their nature, they are evolving complex networks. Community structure identification in these networks is a hot topic; especially because of the popularity of social networks in daily life. Community structure is important in friendship network, e-mail traffic network etc. It is important for security, virus protection too. Grabbing community structure from some raw data is terrible; ie identifying community structure from e-mail logs in a company. However there will be many commercial products in the following years because the globe is not a safe place anymore and governments will follow suspects and their communities from their phone calls, e-mail traffic even if from chat logs. At this point, if a node in the network is known(here the node is a person), then the whole community (which may be a crime network) can easily be identified.

The work is hard. Currently I am dealing with Mark Newman's Fast community detection algorithm. Thanks to him, he provides many useful ideas however implementation of the algorithm for huge networks is not so easy. JUNG (http://jung.sourceforge.net) can also be used for complex network analysis but it seems very difficult to combine my code with JUNG libraries.