Towards an Information Theory of Complex Networks - Statistical Methods and Applications

For over a decade, complex networks have steadily grown as an important tool across abroad array of academic disciplines, with applications ranging from physics to social media.A tightly organized collectionofcarefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities.The book'smajor goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks. This volume is the first to present a self-contained, comprehensive overview of information-theoretic modelsof complex networks with an emphasis on applications. As such, itmarks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networksfor allscientific disciplines andcan serve asa valuable resource foradiverse audience of advanced students and professional scientists.While it is primarilyintendedas a reference for research,the bookcould also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.