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Application Presentation. Zhuhua Cai 12/08/2008. What’s social network?. Central control maintaining information Security assurance Many participants: sharing content Video, Image, Text Skype Many links to friends Nature: peer-to-peer with central control and interface

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  1. Application Presentation Zhuhua Cai 12/08/2008

  2. What’s social network? • Central control • maintaining information • Security assurance • Many participants: sharing content • Video, Image, Text • Skype • Many links to friends • Nature: peer-to-peer with central control and interface • Famous SNS • Facebook, Youtube, Youku, Xiaonei, Myspace, etc.

  3. Composition G=<V, E> • V, users • Pseudonym, in many times, it is the real name of the user • Problem: Sybil Attack • E, links • Sources: real-world acquaintance, online acquaintance, business contact. • Sharing some interests, Or trust each other • Friends of friends links: access control of privacy • Groups • Interest Group • Access control: manager, or free of its members

  4. Content access • Locality • Browse content from friend more frequently • Distribution of content access • Following links: 80.6% • Search Engine: 6.3% • Links from external Web: 13.1% • Potential of Social Networks • Online sharing services • Web search tools • Skype

  5. Potentials • Potentials of • Online sharing services • Re, SybilGuard, SybilLimit, SumUp, Ostra • Web search tools • Google Co-op • Yahoo! My Web 2.0 • Skype (Future internet) • Other disciplines • Politics, Economy

  6. Prerequisites • SCC: strongly connected component • Random networks. • Short path among nodes • Power-law networks. • Probability of a nodes has degree k: proportional to k^{-r} • r: power-law coefficient • Scale-free networks • High-degree connects to high-degree • Small world • Small diameter • High clustering

  7. Methodology(1) • WCC of four websites • Crawling • BFS • overestimate node degree • underestimate symmetry • DFS • Using only forward links

  8. Table

  9. Methodology(2) • Flickr • Forward link • Using samples proves the completeness of WCC • LiveJournal • Forward link and Reverse Link • completeness • Orkut • No sharing content • HTML scraping • Youtube • Forward link

  10. Measurement results(1) • Link symmetry • WEB • not very symmetrical: cnn.com • Suitable for Pagerank • Social networks • Symmetrical with high probability • Reasons: • Reciprocity • Central control informs the incoming links • Results: reducing diameter, • increasing connectivity

  11. Measurement results(2) • Degree: Power-law • Majority nodes: small degree; reversely • Orkut: only 11.3% (BFS); • WEB: similarity between in an out

  12. Measurement results(3) • 5% nodes: 75% incoming links but 25% outgoing links • Social networks: very similar • 1% of nodes in-degree 65% overlap with out-degree • For web: 20%

  13. Measurement results(4) • Path lengths and diameter • Web path avg. length from 16.12 -> 7 if symmetrical

  14. Measurement results(5) • JDD: joint degree distribution (JDD) • Approximated by degree correlation function knn

  15. JDD • Increasing knn denotes the connections among high degree nodes • Youtube is exceptional • Scale-free behavior • High-degree nodes connects high-degree nodes • Flickr: 0.202 • LiveJournal:0.179 • Orkut: 0.072 • Youtube: -0.033 • WEB: negative coauthor Ship networks: positive

  16. Core(1) • A set of nodes satisfying: • Removing the core -> many small disconnected clusters • Strongly connected with a small diameter

  17. Core(2) • Percentage of the tops nodes in the core

  18. Clustering Coefficient • The number of directed links among neighbors divided by N(N-1)

  19. Relation between Clustering Coefficient and out-degree

  20. Groups(1) • Distribution • 8% nodes in Youtube, 61% nodes in LiveJournal • Tightly clustered communities

  21. Groups(1) • Small groups clustered more than large groups

  22. Discussion • Core • viruses disseminate more quickly • Convenient for software distribution • Like Gnutella • Trust • Function of path between the source and target node • Users in the core appear many paths • Malicious in the joint path may skew trust computation • Fringe nodes will not be trusted

  23. Summary • The composition of social networks • Properties • Power-law • Scale-free • Small world

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