Encyclopedia of Social Network Analysis and Mining

Living Edition
| Editors: Reda Alhajj, Jon Rokne

History and Evolution of Social Network Visualization

  • Carlos D. Correa
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7163-9_102-1



Social Network

A network formed by a group of actors and their interactions. It is often represented as a graph

Vertex (Node)

A fundamental unit of a social network. Can be featureless or can be associated with values, concepts, or classes of objects

Edge (Link)

A fundamental unit of a social network that connects two vertices or nodes. Can be directed or undirected


Also known as node-link diagram. A graphical representation of a social network, often attaching a glyph or geometric figure to each node and a line segment or curve between the glyphs connected by an edge

Node Degree

Number of connections of a node in a network. In a directed graph, it can be decomposed in two components, the in-degree and out-degree of a node


A measure of importance of a node, defined as a function of the shortest paths passing through the node. A similar measure, called the edge betweenness, exists for...

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This chapter was prepared by LLNL under Contract DE-AC52-07NA27344. The author is now affiliated with Google Inc.


  1. Albert R, Barabási AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97MathSciNetCrossRefzbMATHGoogle Scholar
  2. Aris A, Shneiderman B (2007) Designing semantic substrates for visual network exploration. Inf Vis 6(4):281–300CrossRefGoogle Scholar
  3. Batagelj V, Mrvar A (2003) Pajek – analysis and visualization of large networks. In: Graph drawing software. Springer, Berlin, pp 77–103Google Scholar
  4. Bertin J (1983) Semiology of graphics. University of Wisconsin Press, MadisonGoogle Scholar
  5. Borgatti S, Everett MG, Freeman LC (2002) UCINET 6 for windows: software for social network analysis. Analytic Technologies, HarvardGoogle Scholar
  6. Brandes U, Wagner D (2003) Visone – analysis and visualization of social networks. In: Graph drawing software. Springer, Berlin, pp 321–340Google Scholar
  7. Correa C, Crnovrsanin T, Ma KL (2012) Visual reasoning about social networks using centrality sensitivity. IEEE Trans Vis Comput Graph 18(1):106–120CrossRefGoogle Scholar
  8. Cox TF, Cox M (2000) Multidimensional scaling, 2nd edn. Chapman and Hall/CRC, Boca RatonzbMATHGoogle Scholar
  9. Dwyer T, Hong SH, Koschützki D, Schreiber F, Xu K (2006) Visual analysis of network centralities. In: APVis’06: proceedings of the 2006 Asia-Pacific symposium on information visualisation. Tokyo, pp 189–197Google Scholar
  10. Eades P (1984) A heuristic for graph drawing. Congressus Numerantium 42:149–160MathSciNetGoogle Scholar
  11. Forsyth E, Katz L (1946) A matrix approach to the analysis of sociometric data: preliminary report. Sociometry 9(4):340–347CrossRefGoogle Scholar
  12. Freeman L (2000) Visualizing social networks. J Soc Struct 1(1):151–161Google Scholar
  13. Fruchterman TMJ, Reingold EM (1991) Graph drawing by force-directed placement. Softw Pract Exp 21(11):1129–1164CrossRefGoogle Scholar
  14. Furnas GW (1986) Generalized fisheye views. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI’86. Boston, pp 16–23Google Scholar
  15. Furnas GW, Bederson BB (1995) Space-scale diagrams: understanding multiscale interfaces. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI’95. Denver, pp 234–241Google Scholar
  16. George VP, Allen TJ (1989) Netgraphs: a graphic representation of adjacency matrices as a tool for network analysis. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MAGoogle Scholar
  17. Heer J, Boyd D (2005) Vizster: visualizing online social networks. In: INFOVIS’05: proceedings of the 2005 I.E. symposium on information visualization. Minneapolis, p 5Google Scholar
  18. Herman I, Melançon G, Marshall MS (2000) Graph visualization and navigation in information visualization: a survey. IEEE Trans Vis Comput Graph 6(1):24–43CrossRefGoogle Scholar
  19. Huang ML, Eades P, Cohen RF (1998) WebOFDAV – navigating and visualizing the web on-line with animated context swapping. Comput Netw ISDN Syst 30(1–7):638–642CrossRefGoogle Scholar
  20. Kamada T, Kawai S (1989) An algorithm for drawing general undirected graphs. Inf Process Lett 31(1):7–15MathSciNetCrossRefzbMATHGoogle Scholar
  21. Koren Y (2002) On spectral graph drawing. In: Proceedings of the 9th international computing and combinatorics conference (COCOON’03), Big Sky, Lecture notes in computer science, vol 2697. Springer, Berlin, pp 496–508Google Scholar
  22. Lamping J, Rao R, Pirolli P (1995) A focus+context technique based on hyperbolic geometry for visualizing large hierarchies. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI’95. Denver, pp 401–408Google Scholar
  23. Laumann EO, Guttman L (1966) The relative associational contiguity of occupations in an urban setting. Am Sociol Rev 31:169–178CrossRefGoogle Scholar
  24. Leskovec J, Kleinberg J, Faloutsos C (2007) Graph evolution: densification and shrinking diameters. ACM Trans Knowl Discov Data 1(1):2–42CrossRefGoogle Scholar
  25. Ludwig Herzog von Württemberg (1585) Genealogy. Wikipedia: the free encylopedia. Wikimedia Foundation Inc. 4 Oct 2013. Web. 7 Oct 2013. http://en.wikipedia.org/wiki/Genealogy
  26. Moreno JL, Jennings HH (1934) Who shall survive?: a new approach to the problem of human interrelations. Nervous and Mental Disease Publishing Co, Washington, DCCrossRefGoogle Scholar
  27. Noack A (2003) An energy model for visual graph clustering. In: Graph drawing. Perugia, pp 425–436Google Scholar
  28. Shen Z, Ma KL, Eliassi-Rad T (2006) Visual analysis of large heterogeneous social networks by semantic and structural abstraction. IEEE Trans Vis Comput Graph 12(6):1427–1439CrossRefGoogle Scholar
  29. Wattenberg M (2006) Visual exploration of multivariate graphs. In: CHI’06: proceedings of the SIGCHI conference on human factors in computing systems. Montréal, pp 811–819Google Scholar
  30. Zachary W (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33:452–473CrossRefGoogle Scholar
  31. Zeiliger R (1998) Supporting constructive navigation of web space. In: Proceedings of the workshop personalized and solid navigation in information space. StockholmGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Lawrence Livermore National Laboratory, Center for Applied Scientific ComputingLivermoreUSA

Section editors and affiliations

  • Talel Abdessalem
    • 1
  • Rokia Missaoui
    • 2
  1. 1.telecom-paristechParisFrance
  2. 2.Department of Computer Science and EngineeringUniversité du Québec en Outaouais (UQO)GatineauCanada