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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems

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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems ( online-social-networks-measurement-analysis-and-applications )

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Flickr LiveJournal Orkut 79 YouTube 1,157,827 unknown Jan 15, 2007 4,945,382 4.29 79.1% 30,087 0.25 1,846,198 26.9% Jan 9, 2007 5,284,457 95.4% Dec 9 - 11, 2006 3,072,441 11.3% Oct 3 - Nov 11, 2006 22,613,981 12.24 62.0% 77,402,652 16.97 73.5% 223,534,301 106.1 100.0% Number of users Estimated coverage Dates of crawl Number of links Friends per user Fraction symmetric links Number of groups Memberships per user 103,648 4.62 7,489,073 8,730,859 21.25 106.44 Table 5.1 : High-level statistics of social networking site crawls. participation in shared interest groups also vary by two to three orders of magni- tude. Our analysis later will show that despite these differences, these graphs share a surprisingly large number of key structural properties. 5.2 Link symmetry The fact that links are directed can be useful for locating content in information networks. For example, in the Web graph, search algorithms such as PageRank [122] consider a directed link from a source to a destination as an endorsement of the destination by the source, but not vice-versa. For instance, numerous Web pages point to sites like cnn.com or nytimes.com, but very few pages receive pointers back from these sites. Search engines leverage this to identify reputed sources of

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