Network visualization and problem-solving support: A cognitive fit study |
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Institution: | 1. Northeastern University, 360 Huntington Avenue, 204 Lake Hall, Boston, MA, 02115, USA;2. University of Massachusetts at Amherst, N308 Integrative Learning Center, 650 N. Pleasant Street, Amherst, MA, 01003-1100, USA |
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Abstract: | This study examines the relative effectiveness of four different social network representations for improving human problem-solving accuracy and speed: node-link diagrams, adjacency matrices, tables, and text. Results suggest that visual network representations improve problem-solving accuracy and speed, compared with text. Among the visual representations, tables produced superior problem-solving outcomes for symbolic tasks and link-node diagrams produced superior problem-solving outcomes for spatial tasks. These results partially support a cognitive fit model of problem-solving support. There is not “one best way” to represent network data. Instead, it is important to match network representations and problem-solving tasks. |
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Keywords: | Network visualization Problem-solving Cognitive fit Data visualization |
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