Social Network Analysis, Semantic Web and Learning Networks
description
Transcript of Social Network Analysis, Semantic Web and Learning Networks
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SNA & Semantic Web (and LN)
Rory Sie
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Outline
•Recap
•Semantic Web
•Use for LN
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Recap
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Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
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Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
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Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
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Data storage
• Adjacency matrix (R, UCINET)
• GML/XGMML (Cytoscape, Gephi)
• Pajek Network (Pajek, UCINET)
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Data storage
• Adjacency matrix (R, UCINET)
• GML/XGMML (Cytoscape, Gephi)
• Pajek Network (Pajek, UCINET)
<?xml version="1.0" encoding="UTF-8" standalone="yes"?><graph label="PLN for ID " directed="1"><node id="n26" label="n26"><att type="string" name="PeerName" value="Rory Sie"/></node><node id="n27" label="n27"><att type="string" name="PeerName" value="Adriana Berlanga"/></node><edge id="e0" label="e0" source="n26" target="n27"><att type="string" name="interaction" value="colleague""/>
</edge></graph>
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Data storage
• Adjacency matrix (R, UCINET)
• GML/XGMML (Cytoscape, Gephi)
• Pajek Network (Pajek, UCINET)
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Analysis
But what if you want to do this real-time / online?
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CytoscapeWeb
•http://cytoscapeweb.cytoscape.org
•Cytoscape, but online
•Great for visualization
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Connect R to web
RemoteREngine package
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Web 1.0
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Web 2.0
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Semantic Web (3.0)
writeswrites
about place
wri
tes
about
resource
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Semantic Web (3.0)
writes
writes
about place
wri
tes
about
resource
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Semantic Web (3.0)
writes
writes
about place
wri
tes
about
resource
learn
s fr
om
friend o
f
mother of
follows
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learning
netw
orks
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
“Rory”“learns from”“Adriana”
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
“Rory”“learns from”“Adriana”subject predicate object
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
subject predicate objecttriple“Rory”“learns from”“Adriana”
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Example data
<http://ln.org/person/Rory> <http://ln.org/learns_from> <http://ln.org/person/Adriana>
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
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Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
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Example data
<http://ln.org/person/Rory> <http://ln.org/learns_from> <http://ln.org/person/Adriana>
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SPARQL
SELECT ?tutor
WHERE
{
<http://ln.org/person/Rory> <http://ln.org/learns_from> ?tutor
}
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How can this help us?
•store learning networks data in RDF
•use SNA to analyse network, individuals, communities, topics
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CSCL script and roles
Capuano et al, 2011)
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SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree = 5
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SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<family> = 2
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SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<friend> = 1
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SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<peer learner> = 2
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SPARQL n-degreeselect ?y count(?x) as ?degree where{{?x $path ?yfilter(match($path, star(param[type])))filter(pathLength($path) <= param[length]) } UNION{?y $path ?xfilter(match($path, star(param[type]))) filter(pathLength($path) <= param[length]) }} group by ?y
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Summary
Semantic Web and Social Network Analysis help us make sense of different types of data that are in a social network
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http://www.open.ou.nl/rse
openrory, maisonpoublon
Rory Sie
openrse
http://nl.linkedin.com/in/rorysie
thebigbangrory.blogspot.com
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References
• R project (http://www.r-project.org/)
• UCINET (https://sites.google.com/site/ucinetsoftware/home)
• Gephi (http://gephi.org/)
• Cytoscape (http://www.cytoscape.org)
• Capuano, N., Laria, G., Mazzoni, E., Pierri, A., & Mangione, G. R. (2011). Improving Role Taking in CSCL Script Using SNA and Semantic Web. 2011 IEEE 11th International Conference on Advanced Learning Technologies, 636-637. Ieee. doi:10.1109/ICALT.2011.197
• Berners-lee, B. T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American.
• Guillaume Ereteo’s PhD defense (http://www.slideshare.net/ereteog/phd-defense-semantic-social-network-analysis)
• Microformats (http://microformats.org/)