Social network visualizations of streaming data: Design and use considerations

Abstract

Abstract. Understanding networks of people linked by some common factor is an important task in many domains. Most commonly, a user creates a visualization of social interactions to see the patterns of interactions between individuals, and then used to find and identify important groups. Networks of individuals and links between them form graphs that vary with time and importance. Visualizing the changes in social networks over time is a non-trivial design task, imposing interesting demands on the visualization and interaction model. In this paper we briefly analyze the user requirements for interactive visualizations of streaming social network data. We find that these continuously updated, dynamic displays need: (1) controls that permit time-based control of the visualization, including pausing, restarting and variable speed playback of the data, (2) the ability to continue importing and processing streamed information even the display is paused, (3) a visually represented method to track changes in the displays over time, (4) interaction methods to allow drilldown from the visualization to original source data, and (5) information extraction from the displayed social network. We describe our visualization tool, SSNV, showing how it embodies these interaction requirements

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