City Research Online

Abstract

Visualizing network data is applicable in domains such as biology, engineering, and social sciences. We report the results of a study comparing the effectiveness of the two primary techniques for showing network data: node-link diagrams and adjacency matrices. Specifically, an evaluation with a large number of online participants revealed statistically significant differences between the two visualizations. Our work adds to existing research in several ways. First, we explore a broad spectrum of network tasks, many of which had not been previously evaluated. Second, our study uses a large dataset, typical of many real-life networks not explored by previous studies. Third, we leverage crowdsourcing to evaluate many tasks with many participants.

Publication Type:	Article
Additional Information:	This is a post-peer-review, pre-copyedit version of an article published in Frati F., Ma KL. (eds) Graph Drawing and Network Visualization. GD 2017. Lecture Notes in Computer Science, vol 10692. Springer, Cham. The final publication is available at Springer http://dx.doi.org/978-3-319-73915-1
Departments:	School of Science & Technology > Computer Science School of Science & Technology > Computer Science > giCentre

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