![](bg6.png)
5.3 Community Visualization
The visualization is a significant part of
KANGAROO, also a very difficult part. In this
section, we show the community visualization which
is most tough task for the presentation layer.
After community detection on Karate graph, the
visualization of the communities is represented in
Figure 9 which is clear and intelligible to distinguish
the different nodes among all communities. In Figure
10, we represent a more beautiful graph which
contains 12 communities in diverse colors.
6 CONCLUSIONS AND FUTURE
WORK
Motivated by recently increasing request for the large
scale social network analysis, in this paper, we
introduce our solution, KANGAROO based on
distributed system, and report how to construct it
using the open-source Hadoop project, also the
advantages of this system, including the ability to
analyze the huge scale social network and the high
performance with linear speedup ratio.
We employ a huge scale real-world network with
ten million nodes and edges to analyze with
KANGAROO, including basic statistics, community
detection and community visualization. In these cases,
we do not only show the result of our algorithms but
also the speedup ratio of our system.
At present, KANGAROO is an on-going system,
our future work will continue in the construction of
this system, especially the computing modes and
algorithms for large scale social network, scalability
and performance. Fundamentally, we hope
KANGAROO can serve as a practical social network
analysis framework for huge scale real-world
network.
ACKNOWLEDGEMENTS
This work is supported by the National Science
Foundation of China (Grant No.60905025, 90924029,
61074128), National High Technology Research and
Development Program of China
(No.2009AA04Z136), National Key Technology
R&D Program of China (2006BAH03B05) and the
Fundamental Research Funds for the Central
Universities.
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