The large-scale structure of networks
The large-scale structure of networks
A discussion of some of the recurring patterns and structures revealed when we apply the concepts developed in previous chapters to the study of real-world networks
The previous chapters looked at different types of natural and man-made networks and techniques for determining their structure, the mathematics used to represent networks formally, and the measures and metrics used to quantify network structure. This chapter combines what have been learned so far, applying theoretical ideas and measures to empirical network data to get a picture of what networks look like in the real world. It shows that there are a number of common recurring patterns seen in network structures, patterns that can have a profound effect on the way networked systems work. Among other things, the chapter discusses component sizes, path lengths and the small-world effect, degree distributions and power laws, and clustering coefficients. Exercises are provided at the end of the chapter.
Keywords: network data, network analysis, component sizes, path lengths, small-world effect, degree distributions and power laws, clustering coefficients
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