Evaluation of the Copycat Model for Predicting Complex Network Growth

We deal here with the issue of complex network evolution. In particular, we propose the use of the Copycat Model as a framework to predict the dynamic behavior of networks. This model has the ability to dynamically adjust the topological properties step by step during the network’s growth. We test the methodology with three networks, an artificial net called popularity vs. similarity and two real ones Manufacturing Emails Network and Slashdot threads Network. The results show that the methodology is able to correctly predict network’s evolution reproducing several network properties.

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