Visualizing Network Data

  • Eric D. Kolaczyk
  • Gábor Csárdi
Chapter
Part of the Use R! book series (USE R, volume 65)

Abstract

Up until this point, we have spoken only loosely of displaying network graphs, although we have shown several examples already. Here in this chapter we consider the problem of display in its own right. Techniques for displaying network graphs are the focus of the field of graph drawing or graph visualization. Such techniques typically seek to incorporate a combination of elements from mathematics, human aesthetics, and algorithms. After a brief characterization of the elements of graph visualization in Sect. 3.2, we look at a number of ways to lay out a graph, in Sect. 3.3, followed by some ways to further decorate such layouts, in Sect. 3.4. We also look quickly at some of the unique challenges posed by the problem of visualizing large network graphs in Sect. 3.5. Finally, in Sect. 3.6, we describe options for producing more sophisticated visualizations than those currently possible using R.

Keywords

Editing Cyan 

References

  1. [21]
    K. Boyack, R. Klavans, K. Börner, Mapping the backbone of science. Scientometrics 64(3), 351–374 (2005)CrossRefGoogle Scholar
  2. [31]
    W. Cleveland, The Elements of Graphing Data (Wadsworth, Monterey, 1985)Google Scholar
  3. [32]
    W. Cleveland, Visualizing Data (Hobart Press, Summit, 1993)Google Scholar
  4. [42]
    G. Davidson, B. Wylie, K. Boyack, Cluster stability and the use of noise in interpretation of clustering. IEEE Symposium on Information Visualization, 2002, pp. 23–30Google Scholar
  5. [46]
    G. di Battista, P. Eades, R. Tamassia, I. Tollis, Graph Drawing (Prentice Hall, Englewood Cliffs, 1999)MATHGoogle Scholar
  6. [60]
    T. Fruchterman, E. Reingold, Graph drawing by force-directed placement. Software Pract. Ex. 21(11), 1129–1164 (1991)CrossRefGoogle Scholar
  7. [66]
    S. Gopal, The evolving social geography of blogs. In Societies and Cities in the Age of Instant Access, ed. by H. Miller (Springer, Berlin, 2007), pp. 275–294CrossRefGoogle Scholar
  8. [67]
    J. Gross, J. Yellen, Graph Theory and Its Applications (Chapman & Hall/CRC, Boca Raton, 1999)MATHGoogle Scholar
  9. [85]
    T. Kamada, S. Kawai, An algorithm for drawing general undirected graphs. Inform. Process. Lett. 31(1), 7–15 (1989)CrossRefMATHMathSciNetGoogle Scholar
  10. [89]
    M. Kaufmann, D. Wagner (eds.), Drawing Graphs (Springer, Berlin, 1998)Google Scholar
  11. [91]
    E. Kolaczyk, Statistical Analysis of Network Data: Methods and Models (Springer, New York, 2009)CrossRefGoogle Scholar
  12. [106]
    S. Martin, W. Brown, R. Klavans, K. Boyack, DrL: distributed recursive (graph) layout. SAND Reports, Technical Report 2936, 2008Google Scholar
  13. [139]
    E. Tufte, The Visual Display of Quantitative Information (Graphics Press, Cheshire, 1983)Google Scholar
  14. [140]
    J. Tukey, Exploratory Data Analysis (Addison-Wesley, New York, 1977)MATHGoogle Scholar
  15. [149]
    W. Zachary, An information flow model for conflict and fission in small groups. J. Anthropol. Res. 33(4), 452–473 (1977)Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Eric D. Kolaczyk
    • 1
  • Gábor Csárdi
    • 2
  1. 1.Department of Mathematics and StatisticsBoston University ProfessorBostonUSA
  2. 2.Department of StatisticsHarvard University Research AssociateCambridgeUSA

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