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Distinguishing between Different Mechanisms of Network Evolution using Network Motifs and Machine Learning

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thesis
posted on 01.05.2014, 00:00 by Manojit Nandi
In this thesis, I will introduce two methodological tools for understanding the evolution of social networks. Using a mathematical representation of social networks based on covariance matrices, I demonstrate machine learning algorithms can use these representations of networks to properly classify networks based on their evolution mechanism with high accuracy. I also show the over-expression of particular network motifs can be used to distinguish between different network evolution processes.

History

Date

01/05/2014

Advisor(s)

Russell Golman

Department

Social and Decision Sciences