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Introduction to the Modeling and Analysis of Complex Systems

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Chapter 17Dynamical Networks II: <strong>Analysis</strong> <strong>of</strong>Network Topologies17.1 Network Size, Density, <strong>and</strong> PercolationNetworks can be analyzed in several different ways. One way is <strong>to</strong> analyze <strong>the</strong>ir structuralfeatures, such as size, density, <strong>to</strong>pology, <strong>and</strong> statistical properties.Let me first begin with <strong>the</strong> most basic structural properties, i.e., <strong>the</strong> size <strong>and</strong> density<strong>of</strong> a network. These properties are conceptually similar <strong>to</strong> <strong>the</strong> mass <strong>and</strong> composition <strong>of</strong>matter—<strong>the</strong>y just tell us how much stuff is in it, but <strong>the</strong>y don’t tell us anything about how<strong>the</strong> matter is organized internally. None<strong>the</strong>less, <strong>the</strong>y are still <strong>the</strong> most fundamental characteristics,which are particularly important when you want <strong>to</strong> compare multiple networks.You should compare properties <strong>of</strong> two networks <strong>of</strong> <strong>the</strong> same size <strong>and</strong> density, just likechemists who compare properties <strong>of</strong> gold <strong>and</strong> copper <strong>of</strong> <strong>the</strong> same mass.The size <strong>of</strong> a network is characterized by <strong>the</strong> numbers <strong>of</strong> nodes <strong>and</strong> edges in it.NetworkX’s Graph objects have functions dedicated for measuring those properties:Code 17.1:>>> g = nx.karate_club_graph()>>> g.number_<strong>of</strong>_nodes()34>>> g.number_<strong>of</strong>_edges()78371

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