Abstract
This paper is focused on the visualization of dynamic social networks, i.e. graphs whose edges model social relationships which evolve during time. In order to overcome the problem of discontinuities of the graphical representations computed by discrete methods, the proposed approach is a continuous one which updates the changes as soon as they happen in the visual restitution. The vast majority of the continuous approaches are restricted to 2D supports which do not optimally match the human perception capabilities. We here present TempoSpring which is a new interactive 3D visualization tool of dynamic graphs. This innovative tool relies on a force-directed layout method to span the 3D space along with several immersive setups (active stereoscopic system/visualization in a dome) to offer an efficient user-experience. TempoSpring has initially been developed in a particular application context: the analysis of sociability networks in the French medieval peasant society.
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References
Archambault D, Munzner T, Auber D (2007) Topolayout: Multi-level graph layout by topological features. IEEE Trans Visual Comput Graph 13:2007
Di-Battista G, Eades P, Tamassia R, Tollis IG (1999) Graph drawing - algorithms for the visualization of graphs. Prentice Hall, Upper Saddle River, NJ
Falkowski T, Bartelheimer J, Spiliopoulou M (2006) Mining and visualizing the evolution of subgroups in social networks. In: WI ’06: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, IEEE Computer Society, pp 52–58
Fernanda B, Viégas, Donath J (2004) Social network visualization: Can we go beyond the graph. In: Workshop on Social Networks for Design and Analysis: Using Network Information in CSCW 2004, pp 6–10
Freeman L (2000) Visualizing social networks. J Soc Struct 1:151–161
Fruchterman TMJ, Reingold EM (1991) Graph drawing by force-directed placement. Software Pract Ex 21(11):1129–1164
Ghoniem M, Fekete JD, Castagliola P (2005) On the readability of graphs using node-link and matrix-based representations: a controlled experiment and statistical analysis. Inform Visual 4(2):114–135
Halpin H, Zielinski D, Brady R, Kelly G (2008) Exploring semantic social networks using virtual reality. In: Proceedings of the 7th International Conference on The Semantic Web, Lecture Notes In Computer Science, vol 5318, pp 599–614
Herman I, Melançon G, Marshall S (2000) Graph visualization and navigation in information visualization: a survey. IEEE Trans Visual Comput Graph 6(1):24–43
Knuth D (1963) Computer-drawn flowcharts. Comm ACM 6:555–563
McCrickard DS, Kehoe CM (1997) Visualizing search results using sqwid. In: Sixth International World Wide Web Conference, ACM Press, pp 51–60
Misue K, Eades P, Lai W, Sugiyama K (1995) Layout adjustment and the mental map. J Visual Lang Comput 6(2):183–210
Puolamäki K, Bertone A (2009) Introduction to the special issue on visual analytics and knowledge discovery. SIGKDD Explorations 11(2):3–4
Rosvall M, Bergstrom CT (2010) Mapping change in large networks. PLoS ONE 5(1)
Sarkar M, Brown MH (1992) Graphical fisheye views of graphs. In: CHI ’92: Proceedings of the SIGCHI conference on Human factors in computing systems, ACM, pp 83–91
Telea A, Ersoy O (2010) Image-based edge bundles: Simplified visualization of large graphs. Comput Graph Forum 29(3):843–852
Ware C, Mitchell P (2008) Visualizing graphs in three dimensions. ACM Trans Appl Percept 5:2–15
Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, Cambridge, New York
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Greffard, N., Picarougne, F., Kuntz, P. (2012). Immersive Dynamic Visualization of Interactions in a Social Network. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_26
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DOI: https://doi.org/10.1007/978-3-642-24466-7_26
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