social network analysis, semantic web and learning networks

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)

htt

p:/

/ww

w.a

g-n

bi.de/r

ese

arc

h/s

wrl

engin

e/

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

}

Result

<http://ln.org/person/Adriana>

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

Questions?rory.sie@ou.nl

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/)