University of Porto, Faculty of Engineering, 2014-09-23. Seminar on Intelligent Systems, Interaction and Multimedia.

1. Community detection in
social networks
Francisco Restivo
fjr@fe.up.pt
http://orcid.org/0000-0002-6173-082X
SSIIM, FEUP, 23-09-2014

2. Networks
• Networks are everywhere
• Social, biological, financial, etc
• Complex networks
• Communities reveal properties of networks
• Communities vs. clusters
• Software tools
• Some project ideas
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7. Players
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8. Barabási Lab
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9. Network Science @ NEU
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10. Amaral Lab
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11. Santa Fe Institute
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12. Labic
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13. FAS Research
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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
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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
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
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.
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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.
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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.
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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.
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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.
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25. Software Tools
• NodeXL
• Gephi
• netvizz
• d3.js
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29. netvizz
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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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31. SNAP
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32. KONECT
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33. Project ideas
• Big data set
• See if communities make sense
• Compare different approaches
• Explain your findings
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34. Thank you!
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