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Hybrid Tree Visualizations for Analysis of Gerrymandering

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Advances in Visual Computing (ISVC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14361))

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Abstract

In the United States, congressional redistricting follows a decennial Census. Gerrymandering can result from selection of district lines regardless of political parties. Understanding the relationships between the multiple dimensions in electoral data is a core goal of gerrymandering analysis. In this paper, we analyze patterns of gerrymandering in election data using a hybrid tree visualization technique that supports both overview and drill-down into a hierarchy of multidimensional relationships in that data. Visualization of hierarchical data is of major interest in information visualization. The technique utilizes a left-to-right node-link diagram to show overall hierarchical structure. Nodes in the diagram depict the levels in the dimensional hierarchy. Each node is rendered as an embedded view that shows its particular dimensional combination. Edges directly connect the contents of the embedded views to provide visual bridges that aid navigation and understanding of dimensional relationships. We demonstrate the utility of this hybrid technique is demonstrated through two use cases. This work aims to both ground and inspire the design of future visualizations for exploring gerrymandering.

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References

  1. All About Redistricting. https://redistricting.lls.edu

  2. Dave’s Redistricting App. https://davesredistricting.org

  3. Amos, B., McDonald, M.P., Watkins, R.: When boundaries collide: constructing a national database of demographic and voting statistics. Public Opin. Q. 81(S1), 385–400 (2017)

    Article  Google Scholar 

  4. Burch, M., Beck, F., Diehl, S.: Timeline trees: visualizing sequences of transactions in information hierarchies. In: Proceedings of the Working Conference on Advanced Visual Interfaces, pp. 75–82 (2008)

    Google Scholar 

  5. Card, S.K., Mackinlay, J.: The structure of the information visualization design space. In: Proceedings of the Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium, VIZ 1997, pp. 92–99. IEEE (1997)

    Google Scholar 

  6. Chen, J., Rodden, J.: Unintentional gerrymandering: political geography and electoral bias in legislatures. Q. J. Polit. Sci. 8(3), 239–269 (2013)

    Article  Google Scholar 

  7. Collins, C., Carpendale, S.: Vislink: revealing relationships amongst visualizations. IEEE Trans. Visual Comput. Graph. 13(6), 1192–1199 (2007)

    Article  Google Scholar 

  8. Conklin, N., Prabhakar, S., North, C.: Multiple foci drill-down through tuple and attribute aggregation polyarchies in tabular data. In: Proceedings of the IEEE Symposium on Information Visualization, pp. 131–134. IEEE (2002)

    Google Scholar 

  9. Crisan, A., Fisher, S.E., Gardy, J.L., Munzner, T.: GEViTRec: data reconnaissance through recommendation using a domain-specific visualization prevalence design space. IEEE Trans. Visual Comput. Graph. 28(12), 4855–4872 (2021)

    Article  Google Scholar 

  10. Crisan, A., Gardy, J.L., Munzner, T.: A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT. Bioinformatics 35(10), 1668–1676 (2019)

    Article  Google Scholar 

  11. DeFord, D.R., Eubank, N., Rodden, J.: Partisan dislocation: a precinct-level measure of representation and gerrymandering. Polit. Anal. 30(3), 403–425 (2021)

    Article  Google Scholar 

  12. Edwards, B., Crespin, M., Williamson, R.D., Palmer, M.: Institutional control of redistricting and the geography of representation. J. Polit. 79(2), 722–726 (2017)

    Article  Google Scholar 

  13. Elmqvist, N., Fekete, J.D.: Hierarchical aggregation for information visualization: overview, techniques, and design guidelines. IEEE Trans. Visual Comput. Graph. 16(3), 439–454 (2009)

    Article  Google Scholar 

  14. Garrison, L., Müller, J., Schreiber, S., Oeltze-Jafra, S., Hauser, H., Bruckner, S.: DimLift: interactive hierarchical data exploration through dimensional bundling. IEEE Trans. Visual Comput. Graph. 27(6), 2908–2922 (2021)

    Article  Google Scholar 

  15. Gleicher, M.: Considerations for visualizing comparison. IEEE Trans. Visual Comput. Graph. 24(1), 413–423 (2017)

    Article  Google Scholar 

  16. Gleicher, M., Albers, D., Walker, R., Jusufi, I., Hansen, C.D., Roberts, J.C.: Visual comparison for information visualization. Inf. Vis. 10(4), 289–309 (2011)

    Article  Google Scholar 

  17. Guerra-Gomez, J., Pack, M.L., Plaisant, C., Shneiderman, B.: Visualizing change over time using dynamic hierarchies: TreeVersity2 and the StemView. IEEE Trans. Visual Comput. Graph. 19(12), 2566–2575 (2013)

    Article  Google Scholar 

  18. Henderson, J.A., Hamel, B.T., Goldzimer, A.M.: Gerrymandering incumbency: does nonpartisan redistricting increase electoral competition? J. Polit. 80(3), 1011–1016 (2018)

    Article  Google Scholar 

  19. Holten, D.: Hierarchical edge bundles: visualization of adjacency relations in hierarchical data. IEEE Trans. Visual Comput. Graph. 12(5), 741–748 (2006)

    Article  Google Scholar 

  20. Javed, W., Elmqvist, N.: Exploring the design space of composite visualization. In: Proceedings of the 2012 IEEE Pacific Visualization Symposium, pp. 1–8. IEEE, Songdo, South Korea (2012)

    Google Scholar 

  21. Levin, H.A., Friedler, S.A.: Automated congressional redistricting. J. Exp. Algorithmics (JEA) 24, 1–24 (2019)

    Article  MathSciNet  Google Scholar 

  22. Levitt, J.: A citizen’s guide to redistricting. Available at SSRN 1647221 (2008)

    Google Scholar 

  23. Mayer, B., Lawonn, K., Donnay, K., Preim, B., Meuschke, M.: VEHICLE: validation and exploration of the hierarchical integration of conflict event data. Comput. Graph. Forum 40(3), 1–12 (2021)

    Article  Google Scholar 

  24. Parks, D.H., Beiko, R.G.: Quantitative visualizations of hierarchically organized data in a geographic context. In: 2009 17th International Conference on Geoinformatics, pp. 1–6. IEEE (2009)

    Google Scholar 

  25. Schöttler, S., Yang, Y., Pfister, H., Bach, B.: Visualizing and interacting with geospatial networks: a survey and design space. Comput. Graph. Forum 40(6), 5–33 (2021)

    Article  Google Scholar 

  26. Schulz, H.J., Schumann, H.: Visualizing graphs-a generalized view. In: Tenth International Conference on Information Visualisation, pp. 166–173. IEEE (2006)

    Google Scholar 

  27. Schulz, H.J.: Treevis. net: a tree visualization reference. IEEE Comput. Graph. Appl. 31(6), 11–15 (2011)

    Google Scholar 

  28. Schulz, H.J., Hadlak, S., Schumann, H.: The design space of implicit hierarchy visualization: a survey. IEEE Trans. Visual Comput. Graph. 17(4), 393–411 (2010)

    Article  Google Scholar 

  29. Shneiderman, B.: Tree visualization with tree-maps: 2-d space-filling approach. ACM Trans. Graph. (TOG) 11(1), 92–99 (1992)

    Article  MATH  Google Scholar 

  30. Stasko, J., Zhang, E.: Focus+ context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations. In: Proceedings of the IEEE Symposium on Information Visualization 2000, pp. 57–65. IEEE (2000)

    Google Scholar 

  31. Stephanopoulos, N.O., McGhee, E.M.: Partisan gerrymandering and the efficiency gap. Univ. Chicago Law Rev. 82, 831 (2015)

    Google Scholar 

  32. Tufte, E.R.: The relationship between seats and votes in two-party systems. Am. Polit. Sci. Rev. 67(2), 540–554 (1973)

    Article  Google Scholar 

  33. Wang Baldonado, M.Q., Woodruff, A., Kuchinsky, A.: Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces, Palermo, Italy, pp. 110–119 (2000)

    Google Scholar 

  34. Woodburn, L., Yang, Y., Marriott, K.: Interactive visualisation of hierarchical quantitative data: an evaluation. In: 2019 IEEE Visualization Conference (VIS), pp. 96–100. IEEE (2019)

    Google Scholar 

  35. Zhao, S., McGuffin, M.J., Chignell, M.H.: Elastic hierarchies: combining treemaps and node-link diagrams. In: Proceedings of the IEEE Symposium on Information Visualization, 2005, INFOVIS 2005, pp. 57–64. IEEE (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Oklahoma City University, Oklahoma City, OK, 73106, USA

    Chenguang Xu

  2. University of Rhode Island, Kingston, RI, 02881, USA

    Sarah M. Brown

  3. University of Florida, Gainesville, FL, 32611, USA

    Christan Grant

  4. University of Oklahoma, Norman, OK, 73019, USA

    Chris Weaver

Authors
  1. Chenguang Xu
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  2. Sarah M. Brown
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  3. Christan Grant
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  4. Chris Weaver
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Corresponding author

Correspondence to Chenguang Xu .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Google Research, Mountain View, CA, USA

    Golnaz Ghiasi

  3. New York University, New York, USA

    Yi Fang

  4. Ben-Gurion University, Be'er Sheva, Israel

    Andrei Sharf

  5. Microsoft Research, Beijing, China

    Yue Dong

  6. The University of Oklahoma, Norman, OK, USA

    Chris Weaver

  7. University of Maryland, Collage Park, MD, USA

    Zhicheng Leo

  8. University of Central Florida, Orlando, FL, USA

    Joseph J. LaViola Jr.

  9. InnerOptic Technology, Hillsborough, NC, USA

    Luv Kohli

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Xu, C., Brown, S.M., Grant, C., Weaver, C. (2023). Hybrid Tree Visualizations for Analysis of Gerrymandering. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2023. Lecture Notes in Computer Science, vol 14361. Springer, Cham. https://doi.org/10.1007/978-3-031-47969-4_7

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  • DOI: https://doi.org/10.1007/978-3-031-47969-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47968-7

  • Online ISBN: 978-3-031-47969-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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