A visualisation technique for large temporal social network datasets in Hyperbolic space

Visualisations of temporal social network datasets have the potential to be complex and require a lot of cognitive input. In this paper, we present a novel visualisation approach that depicts both relational and statistical information of evolving social structures. The underlying framework is implemented by the usage of Hyperbolic Geometry to support focus context rendering. The proposed method guarantees representing prominent social actors through scaling their representations, preserves user's mental map, and provides the user to reduce visual clutter by means of filtering.

[1]  Yehuda Koren,et al.  Topological Fisheye Views for Visualizing Large Graphs , 2005, IEEE Trans. Vis. Comput. Graph..

[2]  Chen Wang,et al.  Dynamic network visualization in 1.5D , 2011, 2011 IEEE Pacific Visualization Symposium.

[3]  Ayellet Tal,et al.  Online Dynamic Graph Drawing , 2008, IEEE Transactions on Visualization and Computer Graphics.

[4]  Richard Brath,et al.  Metrics for effective information visualization , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[5]  Stephen G. Kobourov,et al.  Non-Euclidean Spring Embedders , 2005, IEEE Trans. Vis. Comput. Graph..

[6]  Danny Holten,et al.  Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data , 2006, IEEE Transactions on Visualization and Computer Graphics.

[7]  Peter A. Gloor,et al.  Capturing team dynamics through temporal social surfaces , 2005, Ninth International Conference on Information Visualisation (IV'05).

[8]  Jörn Kohlhammer,et al.  Applying Animation to the Visual Analysis of Financial Time-Dependent Data , 2007, 2007 11th International Conference Information Visualization (IV '07).

[9]  Mark Phillips,et al.  Visualizing hyperbolic space: unusual uses of 4x4 matrices , 1992, I3D '92.

[10]  H. Jennings,et al.  Who Shall Survive , 2007 .

[11]  Eugene Garfield,et al.  Historiographic Mapping of Knowledge Domains Literature , 2004, J. Inf. Sci..

[12]  Tamara Munzner,et al.  Visual Exploration of Complex Time-Varying Graphs , 2006 .

[13]  Helge J. Ritter,et al.  Interactive visualization and navigation in large data collections using the hyperbolic space , 2003, Third IEEE International Conference on Data Mining.

[14]  Niklas Elmqvist,et al.  Perception of Animated Node‐Link Diagrams for Dynamic Graphs , 2012, Comput. Graph. Forum.

[15]  Vladimir Batagelj,et al.  Exploratory Social Network Analysis with Pajek , 2005 .

[16]  Tamara Munzner,et al.  H3: laying out large directed graphs in 3D hyperbolic space , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[17]  Andrew Cumming,et al.  Animated Interval Scatter-Plot Views for the Exploratory Analysis of Large-Scale Microarray Time-Course Data , 2005, Inf. Vis..

[18]  Catherine Plaisant,et al.  TreePlus: Interactive Exploration of Networks with Enhanced Tree Layouts , 2006, IEEE Transactions on Visualization and Computer Graphics.

[19]  Jean-Daniel Fekete,et al.  MatLink: Enhanced Matrix Visualization for Analyzing Social Networks , 2007, INTERACT.

[20]  Noritaka Osawa A multiple-focus graph browsing technique using heat models and force-directed layout , 2001, Proceedings Fifth International Conference on Information Visualisation.

[21]  H. Ritter Self-Organizing Maps on non-euclidean Spaces , 1999 .

[22]  Jean-Daniel Fekete,et al.  NodeTrix: a Hybrid Visualization of Social Networks , 2007, IEEE Transactions on Visualization and Computer Graphics.

[23]  O. Hoeber,et al.  Exploring Web Search Results Using Coordinated Views , 2006, Fourth International Conference on Coordinated & Multiple Views in Exploratory Visualization (CMV'06).

[24]  Heidrun Schumann,et al.  Visualizing time-oriented data - A systematic view , 2007, Comput. Graph..

[25]  Tom A. B. Snijders,et al.  Introduction to stochastic actor-based models for network dynamics , 2010, Soc. Networks.

[26]  Roberto Tamassia,et al.  Difference Metrics for Interactive Orthogonal Graph Drawing Algorithms , 1998, Graph Drawing.

[27]  Hong Zhou,et al.  Geometry-Based Edge Clustering for Graph Visualization , 2008, IEEE Transactions on Visualization and Computer Graphics.

[28]  Kathleen M. Carley,et al.  ORA: Organization Risk Analyzer , 2004 .