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Tables 4.1 Coverageofsocialnetworkingsitecrawls.. . . . . . . . . . . . . 5.1 High-level statistics of social networking site crawls. . . . . . . . 5.2 Power-law coefficient estimates (α) and corresponding . . . 67 ... 79 Kolmogorov-Smirnov goodness-of-fit metrics (D). The Flickr, LiveJournal, and YouTube networks are well approximated by a power-law. ................................ 83 5.3 Average path length, radius, and diameter of the studied networks. The path length between random nodes is very short in social networks. 88 5.4 The observed clustering coefficient, and ratio to random Erd ̈os-R ́eyni graphsaswellasrandompower-lawgraphs. . . . . . . . . . . . . 5.5 Table of the high-level properties of network groups including the fraction of users which use group features, average group size, and averagegroupclusteringcoefficient.................. 6.1 High-levelstatisticsofthenetworkgrowthdata. . . . . . . . . . . .. 94 .. 96 . . 104PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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