The document describes a social bookmarking dataset containing 61,665 posts and ~430,000 tags applied to URLs from November 2009. It aims to facilitate exploratory search of URLs by topic through a graph visualization of the tag relationships using hierarchical aggregation and edge bundling. This approach provides an interactive visualization of interest groups at different levels of granularity and how they evolve over time.

2. Se#ng
• Social
bookmarking
dataset
• URLs
described
by
tags
• Dataset
characteris9cs:
• 61,665
posts
• ~430,000
triples
• Nov
1
–
Nov
30,
2009

3. Goal
• Facilitate
exploratory
search
for
URLs
by
topics
of
interest
• Show
distribu9on
of
dataset
at
different
levels
of
granularity
• Enable
to
inves9gate
groups
of
interests
– What
groups
of
interests
exist?
– Are
they
somehow
related?
– How
do
they
evolve
over
9me?

4. Our
Approach
Graph
Visualiza-on
using
Hierarchical
Aggrega-on
and
Edge
Bundling

5. Why?
• Edge
bundling
methods
proved
useful
for
reducing
cluVer
• Hierarchical
techniques
provide
basis
for
naviga9on
and
level
of
detail
rendering

7. Visual
Representa9on
• Planar
graphical
representa9on
– variable
magnifica9on
– Hierarchical
structure
to
zoom
back
and
forth
– Edge
Bundeling
on
each
hierarchy
level
to
reduce
cluVer
• Nodes
can
be
selected
via
mouse
click
and
edges
connec9ng
to
other
clusters
are
highlighted

9. Take
Away
Messages
• Scalable
graph
viz
• Reveals
groups
of
interest
expressed
by
user
generated
tags
• Hierarchical
graph
viz
layout
enables
analysis
at
different
levels
of
detail
• Edge
bundeling
reduces
cluVer
• Next
step:
Inves9gate
how
clusters
evolve
over
9me

10.
Vedran
Sabol
vsabol@know-­‐center.at
Elisabeth
Lex
elisabeth.lex@tugraz.at
Our
Team
Ralph
Wozelka
rwozelka@know-­‐center.at