semantic social network analysis
DESCRIPTION
TRANSCRIPT
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Semantic Social Network Analysis
Guillaume ERETEO
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Social Network Analysis?
• 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
[Wasserman & Faust 1994] [Scott 2000] [Mika 2007]
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Community detection
Influences the wayinformation is shared[Coleman 1988]
Influences the way actors behave[Burt 2000]
• Global structure• Distribution of actors
and activities
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Centrality: strategic positions
Degree centrality: Local attention
beetweenness centrality:reveal broker "A place for good ideas"[Burt 1992] [Burt 2004]
Closeness centrality: Capacity to communicate
[Freeman 1979]
Community detection: Distribution of actors and activities
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Critical mass
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Balance Theory[Heider 1958]
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Computer networks as social networks
[Wellman 2001]
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web 2.0 amplifies Network effect !
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Semantic social networks
http://sioc-project.org/node/158
Millions of FOAF profiles online
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Social tagging
SCOT
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SNA on the semantic web
Rich graph representations reduced to simpleuntyped graphs in order to apply SNA
[Paolillo and Wright 2006]
Foaf:knows
Foaf:interest
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The Semantic SNA Stack
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Semantic paths in social graphs
likes
ingredient
typemainDish
Food
subclassOf
type
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GérardGérard
FabienFabien
MylèneMylène
MichelMichelYvonneYvonne
father sister
mother
colleague
colleague
parentparentsiblingsibling
mothermotherfatherfatherbrotherbrothersistersister
colleaguecolleague
knowsknows
)( guillaumed familly
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)( guillaumed familly
parentparentsiblingsibling
mothermotherfatherfatherbrotherbrothersistersister
colleaguecolleague
knowsknows
= 3
GérardGérard
FabienFabien
MylèneMylène
MichelMichelYvonneYvonne
father sister
mother
colleague
colleague
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select ?y ?to pathLength($path) as ?length sum(?length) as ?centrality where{
?y $path ?tofilter(match($path, star(param[type]param[type]), 'sa'))
}group by ?y
Closeness centrality
Cc<type>(y)
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add{?x semsna:isMemberOf ?uri
}select ?x ?y genURI(<myorg>) as ?uri from Gwhere { ?x $path ?y filter(match($path, star(param[type]param[type]), 'sa'))}group by any
Parametrized ComponentC<type>(G)
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SemSNA an ontology of SNA
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SemSNA an ontology of SNA
[Conein 2004][Wenger 1998]
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Parametrized n-Degree
construcconstructt{?y semsna:hasInDegreesemsna:hasInDegree _:bO _:bO semsna:isDefinedForPropertysemsna:isDefinedForProperty param[type] _:bO semsna:hasValuesemsna:hasValue ?indegree_:b0 semsna:hasDistance param[length]param[length]
}select ?y count(?x) as ?indegree{
?x $path$path ?y filter(match($path, star(star(param[type]param[type]))))fitler(pathLength($path) <= pathLength($path) <= param[length]param[length])
}group by ?y
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Most popular manager in a work subnetworks
select ?y ?indegree{
?y rdf:type domain:Manager
?y semsna:hasInDegreesemsna:hasInDegree ?z
?z semsna:isDefinedForProperty semsna:isDefinedForProperty rel:worksWithrel:worksWith
?z semsna:hasValuesemsna:hasValue ?indegree
?z semsna:hasDistancesemsna:hasDistance 2
}
order by desc(?indegree)
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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]
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#Guigui
#bk81
#tag27
#bk34
#tag92
#Fabien
Semantic web
Web sémantique
hasTaghasTag
hasBookmark hasBookmark
ShareInterest
MentorOf
label
label
#MichelMentorOf Collaborate
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nameGuillaume Erétéo
organization
mailmentorOf
mentorOf
organizationorganization
manage
contribute
contribute answers