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5.11 Summary We end this chapter with a brief summary of important structural properties of social networks which we observed in our data. • The degree distributions in social networks follow a power-law, and the power- law coefficients for both indegree and outdegree are similar. Nodes with high indegree also tend to have high outdegree. • Social networks appear to be composed of a large number of highly connected clusters consisting of relatively low-degree nodes. These clusters connect to each other via a relatively small number of high-degree nodes. As a consequence, the clustering coefficient is inversely proportional to node degree. • The networks each contain a large, densely connected core. Overall, the network is held together by about 10% of the nodes with highest degree. As a result, path lengths are short, but almost all shortest paths of sufficient length traverse the highly connected core. 101PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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