GLOs

Stolper, Charles D.; Foerster, Florian; Kahng, Minsuk; Lin, Zhiyuan; Goel, Aakash; Stasko, John; Chau, Duen Horng

doi:10.1145/2559206.2581239

Cited by 2 publications

References 14 publications

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GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

Stolper

Kahng

Lin

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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The field of graph visualization has produced a wealth of visualization techniques for accomplishing a variety of analysis tasks. Therefore analysts often rely on a suite of different techniques, and visual graph analysis application builders strive to provide this breadth of techniques. To provide a holistic model for specifying network visualization techniques (as opposed to considering each technique in isolation) we present the Graph-Level Operations (GLO) model. We describe a method for identifying GLOs and apply it to identify five classes of GLOs, which can be flexibly combined to re-create six canonical graph visualization techniques. We discuss advantages of the GLO model, including potentially discovering new, effective network visualization techniques and easing the engineering challenges of building multi-technique graph visualization applications. Finally, we implement the GLOs that we identified into the GLO-STIX prototype system that enables an analyst to interactively explore a graph by applying GLOs.

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GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

Stolper

Kahng

Lin

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants

Hogan

Melville

Phillips

et al. 2016

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

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While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within–subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks.

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GLOs

Cited by 2 publications

References 14 publications

GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants

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