Visualizing weighted networks: a performance comparison of adjacency matrices versus node-link diagrams

McIntire, John P.; Osesina, O. Isaac; Bartley, Cecilia; Tudoreanu, M. Eduard; Havig, Paul R.; Geiselman, Eric E.

doi:10.1117/12.920012

Cited by 3 publications

(2 citation statements)

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“…For simpler tasks, matrix-based visualizations are generally superior for identifying connections and relationships, but for complex path-tracing type-tasks, a network diagram is sometimes a necessity (as these tasks are barely possible with the matrix format). Figure 1 below is an example from a paper at this year's SPIE conference 16 . …”

Section: Techniquesmentioning

confidence: 98%

Why social network analysis is important to Air Force applications

et al. 2012

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Social network analysis is a powerful tool used to help analysts discover relationships amongst groups of people as well as individuals. It is the mathematics behind such social networks as Facebook and MySpace. These networks alone cause a huge amount of data to be generated and the issue is only compounded once one adds in other electronic media such as e-mails and twitter. In this paper we outline the basics of social network analysis and how it may be used in current and future Air Force applications.

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Section: Techniquesmentioning

confidence: 98%

Why social network analysis is important to Air Force applications

et al. 2012

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“…Although an empirical evaluation of flow mapping has not been explicitly addressed in cartography, studies in the graph visualization community 4–12 evaluated readability and aesthetics of graph layouts and suggested various principles such as minimizing edge crossings, maintaining large crossing angles, and obtaining symmetrical layouts. The heuristics learned for general graph drawing can only give a very limited guidance for flow map design.…”

Section: Introductionmentioning

confidence: 99%

Design and evaluation of line symbolizations for origin–destination flow maps

Koylu

Guo

2016

Information Visualization

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We present the results of a user study comparing variants of commonly used line symbolizations for directed origin-destination flow maps. Our design and evaluation consisted of five line symbolizations that employ a combination of following visual variables: arrowheads, origin-destination coloring (color hue, and value), line shortening, line width, tapered edges (varying width from wide to narrow, and narrow to wide), and curvature asymmetry and strength. To guide our evaluation, we used a task-by-type typology and chose four representative tasks that are commonly used in flow map reading: identifying dominant direction of flows, flows with the highest magnitude (volume), spatial focusing of long flows toward a destination, and clusters of high netexports (net-outflow). We systematically analyzed user responses and task performance which we measured by task completion time and accuracy. We designed a web-based flow mapping and testing framework and recruited the participants from Amazon Mechanical Turk. To demonstrate the application and user experiment, we used 16 commodity flow data sets in the United States from 2007 and systematically rotated the layouts to evaluate the effect of layout orientation. From this study, we can conclude that there is potential usefulness for all of the five symbolizations we tested; however, the influence of the design on performance and perception depends on the type of the task. Also, we found that data and layout orientation have significant effects on performance and perception of patterns in flow maps which we attribute to the change in visual saliency of node and flow patterns in relation to the way users scan the map. We recommend that the choice of line symbolization should be guided by a task taxonomy which end users are expected to perform. We discuss various design trade-offs and recommendations and potential future work for designing and evaluating line symbolizations for flow mapping.

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