14. Community Detection
• Communities and clusters are different
• Network data is related to graph properties
• Real world data is big
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15. Betweenness
• Find the shortest paths between all pairs of
nodes and count how many run along each
edge
• Remove edge with greatest betweenness and
see if there are disconnected components
• Also, random walk betweenness
SSIIM, FEUP, 23-09-2014 15
16. Modularity
• Compares number of edges with number of
edges of a random network
k
i
k
1
j
P
• Maximize Q is NP-hard
P
SSIIM, FEUP, 23-09-2014 16
j
,g
i
g
ij
ij
ij
A
2m
Q
2m
ij
17. Clauset-Newman-Moore
A hierarchical agglomeration algorithm for detecting community
structure which is faster than many competing algorithms.
Its running time on a network with n vertices and m edges is
O(md log n) where d is the depth of the dendrogram describing the
community structure.
SSIIM, FEUP, 23-09-2014 17
19. Wakita-Tsurumi
CNM algorithm does not scale well and its use is practically limited to
networks whose sizes are up to 500,000 nodes.
A simple heuristics that attempts to merge community structures in a
balanced manner can dramatically improve community structure
analysis.
SSIIM, FEUP, 23-09-2014 19
21. Girvan-Newman
A property that is found in many networks, the property of community
structure, in which network nodes are joined together in tightly knit
groups, between which there are only looser connections.
We propose a method for detecting such communities, built around
the idea of using centrality indices to find community boundaries.
SSIIM, FEUP, 23-09-2014 21
23. Chinese Whispers [Biemann]
• a
Randomized graph-clustering algorithm, which is time-linear in the
number of edges.
It can be viewed as a simulation of an agent-based social network.
SSIIM, FEUP, 23-09-2014 23
24. Link communities [Ahn et al]
Communities in networks often overlap such that nodes
simultaneously belong to several groups.
Meanwhile, many networks are known to possess hierarchical
organization, where communities are recursively grouped into a
hierarchical structure.
SSIIM, FEUP, 23-09-2014 24
30. Datasets
I keep my collection here
https://sites.google.com/site/frestivo/networked-life/databases
There is another in Quora
Where can I find large datasets open to the public?
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