Luis H. Favela
University of Central Florida
Network theory arguably has its origins in Euler’s (1741) graph theory, which was first developed in the mid-1700s to solve the Königsberg bridge problem. Since then, the basic units of graph theory—vertices and edges—have been utilized by a number of scientific disciplines to describe and analyze a wide variety of phenomena. Mark Newman begins his clear and comprehensive introduction to networks with a sampling of various kinds that have been studied: information networks such as the World Wide Web, biological networks such as neural connections, and social networks such as friendships among members of a club. As Newman highlights, network theory and methods are utilized not only within but also across scientific disciplines. The interdisciplinary nature of the scientific study of networks is a double-edged sword. On the one hand, it fosters the cross-pollination of ideas and methods across fields—for example, applying methods used to study computer networks to the investigation of brain networks (cf., Sporns, 2011). On the other hand, such interdisciplinarity can result in confusion and misapplication of theory and methods. Accordingly, Newman’s goal in “Networks: An Introduction” is to synthesize the current state of network theory into a “consistent language and notation” (2010, p. x, Preface). This is no easy task, but Newman gives an admirable attempt that is successful in many ways.
Keywords Networks  Computational Modeling  Modeling
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