A Regularized Graph Layout Framework for Dynamic Network Visualization

Details A Regularized Graph Layout Framework for Dynamic Network Visualization A Regularized Graph Layout Framework for Dynamic Network Visualization

2012-02-27

arxiv.org/abs/1202.6042v1

Computer Science

Social and Information Networks

Supporting material (animations and MATLAB toolbox) available at http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_2012

Scientific paper

Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence of static graph layouts. In addition to providing a visual representation of the network topology at each time step, the sequence should preserve the mental map between layouts of consecutive time steps to allow a human to interpret the temporal evolution of the network. In this paper, we propose a framework for dynamic network visualization using regularized graph layouts. Regularization encourages stability of the layouts over time, thus preserving the mental map. The proposed framework involves optimizing a modified cost function that augments the cost function of a static graph layout algorithm with a grouping penalty, which encourages nodes to stay close to other nodes belonging to the same group, and a temporal penalty, which encourages smooth movements of the nodes over time. We introduce two dynamic layout algorithms under this framework, namely dynamic multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL), that are regularized versions of their static counterparts. We apply the proposed algorithms on several data sets to illustrate the importance of regularization for producing interpretable visualizations of dynamic networks.

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