Fall 2010 to Spring 2018
My dissertation research on network visualization literacy included an opinion survey to identify prominent issues in network visualization comprehension and a large-scale user study of the comprehension of network visualizations.
Surveyed 51 network science researchers to identify target visualization features
Created a series of visualizations with systematic manipulations in numerical and graphical properties
Constructed a series of quantitative network visualization analysis tasks
Recruited hundreds of subjects to complete online test of network visualization comprehension
Developed R scripts to process sample network datasets, conduct network statistics and clustering algorithms, generate test visualizations, process participant response data, apply mixed effects models, and visualize results
Zoss, Angela M. (2018). Network Visualization Literacy: Task, Context, and Layout (Doctoral dissertation). Supervised by Dr. Katy Börner. School of Informatics, Computing, and Engineering, Indiana University: Bloomington, IN.
NetVisLit Repository, including analysis code and presentation slides
Zoss, Angela M., Maltese, Adam, Uzzo, Stephen Miles and Börner, Katy. (2018). Network Visualization Literacy: Novel Approaches to Measurement and Instruction. In Cramer, Catherine, Porter, Mason A., Sayama, Hiroki, Sheetz, Lori and Uzzo, Stephen Miles (Eds.), Network Science In Education (pp. 169-187). : Springer International Publishing. doi:[10.1007/978-3-319-77237-0_11](https://dx.doi.org/10.1007/978-3-319-77237-0_11)
Zoss, Angela M. (March 23, 2018). [Network Visualization Literacy]https://github.com/amzoss/netvislit/blob/master/Zoss-VFF-03-23-18.pdf). Presentation at Duke University Visualization Friday Forum, Durham, NC. video
Zoss, Angela M. (November 1, 2017). Network Visualization Literacy. Presentation at Indiana University Network Science Institute Open Science Forum, Bloomington, IN.
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Text and figures are licensed under Creative Commons Attribution CC BY-SA 4.0. Source code is available at https://github.com/amzoss/amzoss.github.io, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".