SNA & Semantic Web (and LN)
Rory Sie
Outline
•Recap
•Semantic Web
•Use for LN
Recap
Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
Network measures
•network: density, connectivity, centralization
•community: factions, cliques
•individual: betweenness, degree, closeness
Data storage
• Adjacency matrix (R, UCINET)
• GML/XGMML (Cytoscape, Gephi)
• Pajek Network (Pajek, UCINET)
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>
Data storage
• Adjacency matrix (R, UCINET)
• GML/XGMML (Cytoscape, Gephi)
• Pajek Network (Pajek, UCINET)
Analysis
But what if you want to do this real-time / online?
CytoscapeWeb
•http://cytoscapeweb.cytoscape.org
•Cytoscape, but online
•Great for visualization
Connect R to web
RemoteREngine package
Web 1.0
Web 2.0
Semantic Web (3.0)
writeswrites
about place
wri
tes
about
resource
Semantic Web (3.0)
writes
writes
about place
wri
tes
about
resource
Semantic Web (3.0)
writes
writes
about place
wri
tes
about
resource
learn
s fr
om
friend o
f
mother of
follows
learning
netw
orks
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
“Rory”“learns from”“Adriana”
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
“Rory”“learns from”“Adriana”subject predicate object
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
subject predicate objecttriple“Rory”“learns from”“Adriana”
Example data
<http://ln.org/person/Rory> <http://ln.org/learns_from> <http://ln.org/person/Adriana>
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
Knowledge Representation
•RDF
•Triple store (e.g. Sesame)
•Query language (e.g. SPARQL)
Example data
<http://ln.org/person/Rory> <http://ln.org/learns_from> <http://ln.org/person/Adriana>
SPARQL
SELECT ?tutor
WHERE
{
<http://ln.org/person/Rory> <http://ln.org/learns_from> ?tutor
}
How can this help us?
•store learning networks data in RDF
•use SNA to analyse network, individuals, communities, topics
CSCL script and roles
Capuano et al, 2011)
SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree = 5
SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<family> = 2
SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<friend> = 1
SemWeb, LNs and SNA
peer learner
peer learner
friend
father
mother
adapted from Ereteo
degree<peer learner> = 2
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
Summary
Semantic Web and Social Network Analysis help us make sense of different types of data that are in a social network
http://www.open.ou.nl/rse
openrory, maisonpoublon
Rory Sie
openrse
http://nl.linkedin.com/in/rorysie
thebigbangrory.blogspot.com
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/)