Initial Positioning Method for Online and Real-Time Dynamic Graph Drawing of Time Varying Data

Abstract

Microblogging services generate huge histories that suit animated visualization based on graph drawing, but response speeds are insufficient. This paper proposes an effective updating method for the real-time visualization of time varying data. We propose an initial positioning method by combining Additional Edge Resizing (AER) with Sorted Sequential Barycenter Merging (SSBM). AER resizes edges between existing nodes when new edges are added before updating the visualization. SSBM initially positions multiple new nodes sequentially through priority based on the degree of connections to the existing graph. The proposed method prevents a decrease in readability at data update and achieves fast convergence with high accuracy. Quantitative and qualitative evaluations using the energy function and RMSE are detailed along with some visualization results. A graph drawing tool based on HTML5 is also introduced as an implementation of the proposed method and present some use cases for twitter data.