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SFI Social Networking Application Survey
What are “Social Networks”
Powerlaws Social Networks are “scale free”
Graph Complexity Social graphs are key graphs, but there are other graphs, layered and intermingled with the social graphs
Nodes Hubs and Links Node Hub Link
Links have attributes Node Node ,[object Object],[object Object],[object Object],Link Attributes
Page Rank Intelligence
Key Graphs
ELGG SWOT
Saywire SWOT
Open Journal SWOT
Buddypress / Wordpress MU

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Social Network Software - Q3 2009

Notes de l'éditeur

  1. Social Networks are contextual sharing engines that use a social-circles network model aka “social graph”
  2. Cite: Albert-László Barabási Social Networks are “scale free” which means that the associations are based on a power law or Pareto distribution
  3. Scale free networks have three components: Nodes, Hubs (collections of Nodes) and links.
  4. Links have qualitative properties
  5. Google Pagerank is an example of qualitative intelligence Mathematical PageRanks (out of 100) for a simple network (PageRanks reported by Google are rescaled logarithmically). Page C has a higher PageRank than Page E, even though it has fewer links to it; the link it has is of a much higher value. A web surfer who chooses a random link on every page (but with 15% likelihood jumps to a random page on the whole web) is going to be on Page E for 8.1% of the time. (The 15% likelihood of jumping to an arbitrary page corresponds to a damping factor of 85%.) Without damping, all web surfers would eventually end up on Pages A, B, or C, and all other pages would have PageRank zero. Page A is assumed to link to all pages in the web, because it has no outgoing links.
  6. The different software available has biases towards the “Key” graph managed by the tools. Fos SFI, Hub-centric graphs are the appropriate solution, since the SFI content is the Hub.
  7. ELGG Software
  8. Saywire Application Service Provider
  9. Open Journal Peer-review community software
  10. New Kid on the block, Buddypress/Wordpress MU