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Semantic Social Network Analysis

Semantic Social Network Analysis. Guillaume ERETEO. Paul. Peter. friend of. friend of. Jack. Social Network Analysis?. [Wasserman & Faust 1994] [Scott 2000] [Mika 2007]. A science to understand the structure, the interactions and the strategic positions in social networks.

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Semantic Social Network Analysis

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  1. Semantic Social Network Analysis Guillaume ERETEO

  2. Paul Peter friend of friend of Jack Social Network Analysis? [Wasserman & Faust 1994] [Scott 2000] [Mika 2007] • A science to understand the structure, the interactions and the strategic positions in social networks. • Sociograms[Moreno, 1933] • What for? • To control information flow • To improve/stimulate communication • To improve network resilience • To trust

  3. Community detection • Global structure • Distribution of actors and activities Influences the way information is shared [Coleman 1988] Influences the way actors behave [Burt 2000]

  4. Centrality: strategic positions [Freeman 1979] Degree centrality: Local attention Closeness centrality: Capacity to communicate beetweenness centrality: reveal broker "A place for good ideas" [Burt 1992] [Burt 2004]

  5. Critical mass

  6. Balance Theory [Heider 1958]

  7. Computer networks as social networks [Wellman 2001]

  8.  web 2.0 amplifies Network effect !

  9. Semantic social networks Millions of FOAF profiles online http://sioc-project.org/node/158

  10. Social tagging SCOT

  11. SNA on the semantic web [Paolillo and Wright 2006] Rich graph representations reduced to simple untyped graphs in order to apply SNA Foaf:knows Foaf:interest

  12. The Semantic SNA Stack

  13. SemSNA an ontology of SNA

  14. Parametrized n-Degree construct{ ?ysemsna:hasInDegree _:bO _:bO semsna:isDefinedForPropertyparam[type] _:bO semsna:hasValue?indegree _:b0 semsna:hasDistance param[length] } select ?ycount(?x) as ?indegree{ ?x $path ?y filter(match($path, star(param[type]))) fitler(pathLength($path) <= param[length]) }group by ?y

  15. Most popular manager in a work subnetworks select ?y?indegree{ ?y rdf:type domain:Manager ?ysemsna:hasInDegree ?z ?z semsna:isDefinedForProperty rel:worksWith ?z semsna:hasValue?indegree ?z semsna:hasDistance 2 } order by desc(?indegree)

  16. Parametrized Shortest paths for betweenness gb<type>(from, to) PREFIX foaf: <http://xmlns.com/foaf/0.1/> select ?from ?to?between $path pathLength($path) as ?length where{ ?from$path ?to graph $path{?betweenparam[type] ?j} filter(match($path, star(param[type]), 'sa')) optional { ?fromparam[type]::?p ?to } filter(!bound(?p)) filter(?from != ?between) filter(?between != ?to) } group by $path order by ?length

  17. Parametrized Component Cb<type>(G) PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX semsna: <http://ns.inria.fr/semsna/2008/10/13/voc> add{ ?xsemsna:isMemberOf ?uri } select?x ?ygenURI(<myorg>) as ?uri from G where { ?x $path ?y filter(match($path, star(param[type]), 'sa')) } group by any

  18. Current Community detection algorithms • Hierarchical algorithms • Agglomerative (based on vertex proximity): • [Donetti and Munoz 2004] [Zhou Lipowsky, R. 2004] • Divisive (mostly based on centrality): • [Girvan and Newman 2002] [Radicchi et al 2004] • Based on heuristic (modularity, randon walk, etc.) • [Newman 2004], [Pons and Latapy 2005], [Wu and Huberman 2004]

  19. TowardSemantic CommunityDetection mainDish type type ingredient likes subclassOf Food

  20. SemSNA an ontology of SNA [Wenger 1998] [Conein 2004]

  21. Web sémantique label #tag27 #tag92 label Semantic web hasTag hasTag #bk81 #bk34 hasBookmark hasBookmark ShareInterest #Guigui #Fabien MentorOf MentorOf Collaborate #Michel

  22. organization organization organization name Guillaume Erétéo mentorOf mail guillaume.ereteo@orange-ftgoup.com manage answers contribute mentorOf contribute

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