Abstract
In this chapter, we develop a framework for understanding how multidimensional, multilevel data is most effectively conveyed in social network diagrams. We build on work begun in 1994, with a series of explorations of social network visualization with the theme of helping viewers make accurate judgments about network properties. In contrast to contemporary work on layout aesthetics, we were interested in helping viewers with questions that may lie beyond the mathematical graph to the social group that it represented, and that may not be readily available by inspection, unlike path length or degree. We found that different layouts of the same graph had appreciable effects on viewer’s judgment of the importance of individuals with the network individuals or the number of subgroups. In addition, we found that the use of motion to link alternative views of a network had different effects depending on the layouts used. In this chapter we describe and organize some of these results with respect to the long-term goal of aiding human judgment over complex structured data.
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McGrath, C., Blythe, J., Krackhardt, D. (2014). Visualizing Multiple Levels and Dimensions of Social Network Properties. In: Huang, W. (eds) Handbook of Human Centric Visualization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7485-2_20
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DOI: https://doi.org/10.1007/978-1-4614-7485-2_20
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