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Visualization of Large Networks

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Synonyms

Force-directed algorithm; Graph drawing; High-dimensional data; MDS; Multidimensional embedding; Network visualization; Strain model; Stress model

Glossary

Graph Drawing:

The process of constructing a geometric representation of a (mathematical) graph

Force-directed Algorithm:

An algorithm in which the problem of drawing a graph is modeled by a physical system - attractive and repulsive forces on the nodes are calculated, and nodes are moved along the direction of the combined force. This is repeated until the system reaches an equilibrium

Definition

Graphs, or networks, are often used to encapsulate relationship between objects. With the advent of the Internet and increasing use and influence of social media and networks, graphs are appearing with increasing frequency and relevance.

Graph drawing enables a visual representation of graphs. A graph is typically drawn as a node-link diagram, where nodes of the graph are drawn as points, icons, or texts and edges as a line...

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References

  • Akoglu L, McGlohon M, Faloutsos C (2010) Oddball: spotting anomalies in weighted graphs. In: Proceedings of the 14th Pacific-Asia conference on advances in knowledge discovery and data mining (PAKDD 2010), Hyderabad

    Google Scholar 

  • Alper B, Hollerer T, Kuchera-Morin J, Forbes A (2011) Stereoscopic highlighting: 2D graph visualization on stereo displays. IEEE Trans Vis Comput Graph 9:2325–2333

    Google Scholar 

  • Barnes J, Hut P (1986) A hierarchical O(N logN) force-calculation algorithm. Nature 324:446–449

    Google Scholar 

  • Brandes U, Mader M (2012) A quantitative comparison of stress-minimization approaches for offline dynamic graph drawing. In: Proceedings of the 19th international symposium on graph drawing (GD'11). Eindhoven, pp 99–110

    Google Scholar 

  • Brandes U, Pich C (2007) Eigensolver methods for progressive multidimensional scaling of large data. In: Proceedings of the 14th international symposium on graph drawing (GD'06, Karlsruhe). Lecture notes in computer science, vol. 4372. pp 42–53

    MathSciNet  Google Scholar 

  • Davis TA, Hu Y (2011) The University of Florida sparse matrix collection. ACM Trans Math Softw 38:1–25

    MathSciNet  Google Scholar 

  • Di Battista G, Eades P, Tamassia R, Tollis IG (1999) Algorithms for the visualization of graphs. Prentice-Hall, Upper Saddle River

    MATH  Google Scholar 

  • Eades P (1984) A heuristic for graph drawing. Congr Numerantium 42:149–160

    MathSciNet  Google Scholar 

  • Frishman Y, Tal A (2007) Multi-level graph layout on the GPU. J IEEE Trans Vis Comput Graph 13:1310–1319

    Google Scholar 

  • Frishman Y, Tal A (2008) Online dynamic graph drawing. In: Proceedings of the Eurographics/IEEE VGTC symposium on visualization (EuroVis), JIEEE Trans Vis Comput Graph 14:727–740

    Google Scholar 

  • Fruchterman TMJ, Reingold EM (1991) Graph drawing by force directed placement. Softw Pract Exp 21:1129–1164

    Google Scholar 

  • Gansner ER, Hu Y, North S, Scheidegger C (2011) Multilevel agglomerative edge bundling for visualizing large graphs. In: Proceedings of the IEEE pacific visualization symposium, Hong Kong

    Google Scholar 

  • Gansner ER, Hu Y, North S (2012) A Maxent-stress model for graph layout. In: Proceedings of the 5th IEEE pacific visualization symposium, Songdo

    Google Scholar 

  • Gansner ER, Koren Y, North SC (2004) Graph drawing by stress majorization. In: Proceedings of the 12th international symposium on graph drawing (GD'04). Lecture notes in computer science, vol 3383. Springer, Berlin/New York, pp 239–250

    Google Scholar 

  • Gansner ER, Koutsofios E, North S, Vo KP (1993) A technique for drawing directed graphs. IEEE Trans Softw Eng 19:214–230

    Google Scholar 

  • Greengard LF (1988) The rapid evaluation of potential fields in particle systems. MIT, Cambridge/Massachusetts

    MATH  Google Scholar 

  • Hachul S, Junger M (2004) Drawing large graphs with a potential field based multilevel algorithm. In: Proceedings of the 12th international symposium on graph drawing (GD'04, New York). Lecture notes in computer science, vol 3383. Springer, Heidelberg, pp 285– 295

    Google Scholar 

  • Hall KM (1970) An r-dimensional quadratic placement algorithm. Manag Sci 17:219–229

    MATH  Google Scholar 

  • Harel D, Koren Y (2002) Graph drawing by high-dimensional embedding. Lect Notes Comput Sci 2528:207–219

    MathSciNet  Google Scholar 

  • Henry N, Fekete JD, McGuffin MJ (2007) NodeTrix: a hybrid visualization of social networks. IEEE Trans Vis Comput Graph Arch 13:1302–1309

    Google Scholar 

  • Holten D, van Wijk JJ (2009) Force-directed edge bundling for graph visualization. Comput Graph Forum 28:983–990

    Google Scholar 

  • Hu Y (2005) Efficient and high quality force-directed graph drawing. Math J 10:37–71

    Google Scholar 

  • Hu Y, Gansner ER, Kobourov SG (2010) Visualizing graphs and clusters as maps. IEEE Comput Graph Appl 30:54–66

    Google Scholar 

  • Hurter C, Paulovich FV, Cantareiro G, Telea A (2011) Skeleton-based edge bundling for graph visualization. IEEE Trans Vis Comput Graph 17:2364–2373

    Google Scholar 

  • Ingram S, Munzner T, Olano M (2009) Glimmer: multilevel MDS on the GPU. IEEE Trans Vis Comput Graph 15:249–261

    Google Scholar 

  • Jia Y, Hberock J, Garland M, Hart J (2008) On the visualization of social and other scale-free networks. IEEE Trans Vis Comput 14:1285–1292

    Google Scholar 

  • Kamada T, Kawai S (1989) An algorithm for drawing general undirected graphs. Inf Process Lett 31:7–15

    MATH  MathSciNet  Google Scholar 

  • Khoury M, Hu Y, Krishnan S, Scheidegger C (2012) Drawing large graph by low-rank stress majorization. Comput Graph Forum 31:975–984

    Google Scholar 

  • Koren Y, Carmel L, Harel D (2002) Ace: a fast multiscale eigenvectors computation for drawing huge graphs. In: Proceedings of the IEEE symposium on information visualization (InfoVis'02, Boston). IEEE Computer Society, Washington, pp 137–144

    Google Scholar 

  • Leskovec J, Lang K, Dasgupta A, Mahoney M (2009) Community structure in large networks: natural cluster sizes and the absence of large well-defined clusters. Internet Math 6:29–123

    MATH  MathSciNet  Google Scholar 

  • Misue K, Eades P, Lai W, Sugiyama K (1995) Layout adjustment and the mental map. J Vis Lang Comput 6:183–210

    Google Scholar 

  • Monien B, Ramme F, Salmen H (1995) A parallel simulated annealing algorithm for generating 3D layouts of undirected graphs. In: Proceedings of the 16th international symposium on graph drawing (GD'05, Passau). Springer, Heidelberg, pp 90–101

    Google Scholar 

  • Moscovich T, Chevalier F, Henry N, Pietriga E, Fekete J-D (2009) Topology-aware navigation in large networks. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI'09, Boston). ACM, New York, pp 2319–2328

    Google Scholar 

  • Papadopoulos C, Voglis C (2007) Drawing graphs using modular decomposition. In: Proceedings of the 13th international symposium on graph drawing (GD'06, Karlsruhe). Lecture notes in computer science, vol 4372. pp 343–354

    Google Scholar 

  • Quigley A (2001) Large scale relational information visualization, clustering, and abstraction. PhD thesis, Department of Computer Science and Software Engineering, University of Newcastle, Newcastle

    Google Scholar 

  • Sugiyama K, Tagawa S, Toda M (1981) Methods for visual understanding of hierarchical systems. IEEE Trans Syst Man Cybernet (SMC) 11(2):109–125

    MathSciNet  Google Scholar 

  • Torgerson WS (1952) Multidimensional scaling: I. Theory and method. Psychometrika 17:401–419

    MATH  MathSciNet  Google Scholar 

  • Tutte W (1963) How to draw a graph. Proc Lond Math Soc 13:743–768

    MATH  MathSciNet  Google Scholar 

  • van Ham F, Wattenberg M (2008) Centrality based visualization of small world graphs. Comput Graph Forum 27:975–982

    Google Scholar 

  • Walshaw C (2003) A multilevel algorithm for force-directed graph drawing. J Graph Algorithms Appl 7:253–285

    MATH  MathSciNet  Google Scholar 

Recommended Reading

  • Cox TF, Cox MAA (2000) Multidimensional scaling. Chapman and Hall/CRC, Boca Raton

    Google Scholar 

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Hu, Y. (2014). Visualization of Large Networks. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6170-8_44

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