Abstract
Many real-world domains can be represented as complex networks.A good visualization of a large and complex network is worth more than millions of words. Visual depictions of networks, which exploit human visual processing, are more prone to cognition of the structure of such complex networks than the computational representation. We star by briefly introducing some key technologies of network visualization, such as graph drawing algorithm and community discovery methods. The typical tools for network visualization are also reviewed. A newly developed software framework JSNVA for network visual analysis is introduced. Finally,the applications of JSNVA in bibliometric analysis and mobile call graph analysis are presented.
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References
Barabási, A.-L.: Taming complexity. J. Nature Physics. 1, 68–70 (2005)
Börner, K., Sanyal, S., Vespignani, A.: Network Science. In: Cronin, B. (ed.) Annual Review of Information Science & Technology, vol. 41, ch. 12, pp. 537–607. Information Today, Inc., American Society for Information Science and Technology, Medford (2007)
Ye, Q., Wu, B., Wang, B.: JSNVA: a Java Straight-line Drawing Framework for Network Visual Analysis. In: 4th International Conference on Advanced Data Mining and Application, pp. 667–674 (2008)
Thomas, J.J., Cook, K.A.: A Visual Analytics Agenda. IEEE Computer Graphics and Applications 26(1), 10–13 (2006)
Fruchterman, T., Reingold, E.: Graph drawing by force-directed placement. J. Software Practice and Experience 21, 1129–1164 (1991)
Frick, A., Ludwig, A., Mehldau, H.: A fast adaptive layout algorithm for undirected graphs. In: International Symposium on Graph Drawing, pp. 388–403. Springer, Heidelberg (1994)
Gajer, P., Goodrich, M.T., Kobourov, S.G.: A multi-dimensional approach to force-directed layouts of large graphs. In: Marks, J. (ed.) GD 2000. LNCS, vol. 1984, pp. 211–221. Springer, Heidelberg (2001)
Gajer, P., Kobourov, S.G.: GRIP: Graph Drawing with Intelligent Placement. J. Graph Algorithms and Applications 6(3), 203–224 (2002)
Harel, D., Koren, Y.: A fast multi-scale method for drawing large graphs. In: Marks, J. (ed.) GD 2000. LNCS, vol. 1984, pp. 183–196. Springer, Heidelberg (2001)
Kamada, T., Kawai, S.: An algorithm for drawing general undirected graphs. J. Information Processing Letters 31(5), 7–15 (1989)
Koren, Y., Carmel, L., Harel, D.: ACE: AFast Multiscale Eigenvector Computation for Drawing Huge Graphs. J. Multiscale Modeling and Simulation 1(4), 645–673 (2003)
Hachul, S., Jünger, M.: An experimental comparison of fast algorithms for drawing general large graphs. In: Healy, P., Nikolov, N.S. (eds.) GD 2005. LNCS, vol. 3843, pp. 235–250. Springer, Heidelberg (2006)
Heer, J., Card, S.K., Landay, J.A.: Prefuse: a toolkit for interactive information visualization. In: ACM SIGCHI conference on Human factors in computing systems, pp. 421–430. ACM Press, New York (2005)
Assent, I., Krieger, R., Müler, E., Seidl, T.: VISA: Visual Subspace Clustering Analysis. J. ACM SIGKDD Explorations Special Issue on Visual Analytics 9(2), 5–12 (2007)
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Resuable Object-Oriented Sofrware. Addison-Wesley, Reading (1995)
Yee, K.P., Fisher, D., Dhamija, R., Hearst, M.: Animated Exploration of Dynamic Graphs with Radial Layout. In: IEEE International Conference on Information Visualization, pp. 43–50 (2001)
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. J. PNAS 12, 7821–7826 (2002)
Palla, G., Derényi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex networks in nature and society. J. Nature 435, 814–817 (2005)
Cline, M.S., et al.: Integration of biological networks and gene expression data using Cytoscape. Nature Protocols 2, 2366–2382 (2007)
Ye, Q., Zhu, T., Hu, D., Wu, B., Du, N., Wang, B.: Cell Phone Mini Challenge Award: Social Network Accuracy— Exploring Temporal Communication in Mobile Call Graphs. In: IEEE International Symposium on Visual Analytics Science and Technology, pp. 207–208 (2008)
Brin, S., Page, L.: The Anatomy of large-scale Hypertextual Web Search Engine. J. Computer Networks and ISDN Systems 30, 107–117 (1998)
Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004)
Newman, M.E.J.: Analysis of weighted networks. Physical Review E, 056131 (July 20, 2004), arXiv:cond-mat/0407503 v1
Jeffrey Heer, J., Agrawala, M.: Software Design Patterns for Information Visualization. IEEE Transactions on Visualization and Computer Graphics 12(5), 853–860 (2006)
Network Workbench, http://nwb.slis.indiana.edu/
Pajek, http://vlado.fmf.uni-lj.si/
NetDraw, http://www.analytictech.com
netminer, http://www.netminer.com
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Wu, B. et al. (2009). Visual Analysis of Complex Networks and Community Structure. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_93
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DOI: https://doi.org/10.1007/978-3-642-02469-6_93
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