Download Social network analysis and semantic web

BIL489 – Graph Theory
Social Network Analysis
Adapted from slides by Guillaeme Ereteo
Social Networks
A social network is made of actors (people,
organizations, group) that are tied by social links.
Sociograms and graphs
actors are represented by points
(nodes, vertices) and relations by
lines (edges, links, arcs)
Social links
• explicit and declared relations
• interactions between actors
• affiliation between actors
colleague
communicate
like
web
like
undirected networks
well suited for representing
network with symmetric
relationships such as
facebook
directed networks
well suited for representing
network with non reciprocal
relationships such as Twitter
weighted networks
3
1
0.5
1
2
well suited for representing the
intensity of relationships, the
number of interactions (e.g. mails),
or the number of affiliations (e.g.
shared links).
labelled networks
well suited for representing
the type of relationships
family
friend
colleague
follow
follow
father
father
Social network analysis
helps understanding and exploiting the key
features of social networks in order to manage
their assets, their life cycle and predict their
evolution.
What for?
•
•
•
•
To control information flow
To foster communication
To improve network resilience
To trust or not
Diameter
the maximum distance between two actors
Density of links
indicates the cohesion of the network
Centrality: strategic positions
[Freeman 1979]
degree centrality focuses on
the number of relations:
reveal local popularity
Centrality: strategic positions
[Freeman 1979]
closeness centrality focuses on
the proximity of actors:
reveal capacity to communicate
Centrality: strategic positions
[Freeman 1979]
beetweenness centrality focuses
on intermediary actors
reveals brokers and privileged
actor in the information flow
"A place for good ideas"
[Burt 1992] [Burt 2004]
Centrality: strategic positions
eigen vector centrality focuses
on the connections of neighbours
reveals actors that are well
connected
Preferential attachement
Balance Theory
[Heider 1958]
Who has the best betweeness?
this is a matter of semantic
has met
knows in
passing
colleague
works With
friend
works With
Metrics are not sufficient enough
has met
knows in
passing
colleague
works With
friend
works With
examples of vizualisation and
analysis tools
Touchgraph facebook browser
easily vizualize your facebook social network
http://apps.facebook.com/touchgraph
this is mine
Analyze your facebook network
1. Extract it first with netvizz:
http://apps.facebook.com/netvizz
2. Open it with my favorite graph
visualization tool: Gephi
http://www.gephi.org
extract with Netvizz
• choose the information to include
• Save the file
analyze with Gephi
Your network is undirected
select the force layout
compute shortest paths of relations
highlight most popular actors
Highlight brokers
print attributes
NODEXL
• Excel 2007 based social network
visualization and analysis tool
• Homepage http://nodexl.codeplex.com
• Tutorial
http://casci.umd.edu/images/4/46/NodeXL
_tutorial_draft.pdf
Quick overview of the tutorial
"One way to begin using NodeXL is to type in your own
edge list. For example, you might type the name of
people who are friends in each row filling in the Vertex 1
and Vertex 2 columns"
"Click on the Show Graph button (directly above the
graph pane) to show the network of friendships"
"To calculate graph metrics first click on the
Graph Metric button on the Analysis section of
the NodeXL Ribbon."
"Vertex metrics can be mapped onto visual attributes.
The graph legend shows that Degree is mapped to Size
and Betweenness Centrality is mapped to Opacity."
You can now handle your
social capital
The social capital is the "resources embedded in one's
social networks, resources that can be accessed or
mobilized through ties in the networks" [Lin 2008]
http://www.kstoolkit.org/Social+Network+Analysis