semantic social network analysis
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Semantic Social Network Analysis
Guillaume ERETEO
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]
Community detection
Influences the wayinformation is shared[Coleman 1988]
Influences the way actors behave[Burt 2000]
• Global structure• Distribution of actors
and activities
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
Critical mass
Balance Theory[Heider 1958]
Computer networks as social networks
[Wellman 2001]
web 2.0 amplifies Network effect !
Semantic social networks
http://sioc-project.org/node/158
Millions of FOAF profiles online
Social tagging
SCOT
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
The Semantic SNA Stack
Semantic paths in social graphs
likes
ingredient
typemainDish
Food
subclassOf
type
GérardGérard
FabienFabien
MylèneMylène
MichelMichelYvonneYvonne
father sister
mother
colleague
colleague
parentparentsiblingsibling
mothermotherfatherfatherbrotherbrothersistersister
colleaguecolleague
knowsknows
)( guillaumed familly
)( guillaumed familly
parentparentsiblingsibling
mothermotherfatherfatherbrotherbrothersistersister
colleaguecolleague
knowsknows
= 3
GérardGérard
FabienFabien
MylèneMylène
MichelMichelYvonneYvonne
father sister
mother
colleague
colleague
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)
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)
SemSNA an ontology of SNA
SemSNA an ontology of SNA
[Conein 2004][Wenger 1998]
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
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)
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]
#Guigui
#bk81
#tag27
#bk34
#tag92
#Fabien
Semantic web
Web sémantique
hasTaghasTag
hasBookmark hasBookmark
ShareInterest
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label
#MichelMentorOf Collaborate
nameGuillaume Erétéo
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