Visualization of information flows in a very large social network

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Visualization of information flows in a very large social network

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Symposium on Applied Computing archive
Proceedings of the 2009 ACM symposium on Applied Computing table of contents

Honolulu, Hawaii

POSTER SESSION: Poster papers table of contents

Pages 1841-1842

Year of Publication: 2009

ISBN:978-1-60558-166-8

Authors

Shin-gyu Kim	Seoul National University, Seoul, Korea
Hyuck Han	Seoul National University, Seoul, Korea
Kyungho Jeon	Seoul National University, Seoul, Korea
Hyungsoo Jung	Seoul National University, Seoul, Korea
Heon Y. Yeom	Seoul National University, Seoul, Korea

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

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ABSTRACT

In this paper, we present our research result that enables users to navigate a very large social network and to take a look at information flows on the network. To this end, we devise two techniques; (i) mapping a very large social network to a 2-dimensional graph layout, and (ii) exploring the graph to all directions with zooming it in/out. With these methods, we can also look through information flows over social networks.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	IMC 2007 Data Sets, http://socialnetworks.mpi-sws.org/data-imc2007.html.
	2	Daniel Archambault , Tamara Munzner , David Auber, GrouseFlocks: Steerable Exploration of Graph Hierarchy Space, IEEE Transactions on Visualization and Computer Graphics, v.14 n.4, p.900-913, July 2008 [doi>10.1109/TVCG.2008.34]
	3	Travers, Jeffrey, and S. Milgram. An experimental study of the small world problem. Sociometry, 32(4):425--443, 1969.
	4	James Abello , Frank van Ham , Neeraj Krishnan, ASK-GraphView: A Large Scale Graph Visualization System, IEEE Transactions on Visualization and Computer Graphics, v.12 n.5, p.669-676, September 2006 [doi>10.1109/TVCG.2006.120]
	5	F. Wu, B. A. Huberman, L. A. Adamic, and J. R. Tyler. Information flow in social groups. Physica A Statistical Mechanics and its Applications, 337:327--335, June 2004.