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Social Network Visualization, Methods of

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Encyclopedia of Complexity and Systems Science

Glossary

Adjacent:

Two nodes are adjacent to another if there is an edge connecting them.

Arrow:

A line with an arrowhead from one node to another representing a directed link.

Binary relation:

A two valued yes/no or on/off relation.

Bipartite graph:

A graph, B = 〈N, E〉, where N is a finite set of nodes and E is a collection of pairs of nodes in which N is partitioned into two disjoint subsets, N1 and N2, and no edge in E has both end points in the same subset.

Blockmodeling:

A procedure for clustering actors such that the actors in each cluster share similar patterns of ties both within and between clusters.

Connected:

Any two nodes in a graph are said to be connected if there is a path from one to the other; a graph is connected if there is a path connecting every pair of nodes.

Cycle:

Any path that begins and ends at the same node.

Digraph:

A directed graph.

Directed graph:

A graph D = 〈N, A〉 where N is a finite collection of nodes and Ais a set of pairs linked by directed lines...

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Bibliography

  • Alba R (1972) SOCK. Behav Sci 17:326–327

    Google Scholar 

  • Batagelj V, Mrvar A (1998) Pajek-program for large network analysis. Connections 21(2):47–57

    MATH  Google Scholar 

  • Baur M, Benkert B, Brandes U, Cornelsen S, Gaertler M, Köpf B, Lerner J, Wagner D (2001) Visone Software for visual social network analysis. In: International symposium on graph drawing. Vienna, Austria, pp 463–464

    Google Scholar 

  • Bender-deMoll S, McFarland DA (2006) The art and science of dynamic network visualization. J Soc Struct 7:2

    Google Scholar 

  • Beum CO, Brundage EG (1950) A method for analyzing the sociomatrix. Sociometry 13:141–145

    Article  Google Scholar 

  • Biggs NL, Lloyd EK, Wilson RJ (1977) Graph theory 1736–1936. Oxford University Press, Oxford

    MATH  Google Scholar 

  • Bock RD, Husain SZ (1952) Factors of the tele: a preliminary report. Sociometry 15:206–219

    Article  Google Scholar 

  • Borgatti SP (2002) NetDraw: graph visualization software. Analytic Technologies, Harvard

    Google Scholar 

  • Bott E (1957) Family and social network. Tavistock, London

    Google Scholar 

  • Brandes U, Pich C (2007) Eigensolver methods for progressive multidimensional scaling of large data. In: Kaufmann M, Wagner D (eds) Graph Drawing. GD 2006. Lecture Notes in Computer Science, vol 4372, pp 42–53. Springer, Berlin, Heidelberg

    Google Scholar 

  • Brandes U, Raab J, Wagner D (2001) Exploratory network visualisation: simultaneous display of actor status and connections. J Soc Struct 2:4

    Google Scholar 

  • Breiger RL, Boorman SA, Arabie P (1975) An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. J Math Psychol 12(3):328–383

    Article  Google Scholar 

  • Cayley A (1857) On the theory of the analytical forms called trees. Philos Mag 13:19–30

    Article  Google Scholar 

  • Coleman JS, MacRae D (1960) Electronic processing of sociometric data for groups up to 1000 in size. Am Sociol Rev 25:722–727

    Article  Google Scholar 

  • Davis A, Gardner B, Gardner MR (1941) Deep south. University of Chicago Press, Chicago

    Google Scholar 

  • Duquenne V (1987) Contextual implications between attributes and some representation properties for finite lattices. In: Ganter B, Willie R, Wolff K (eds) Beiträge zur Begriffsanalyse. B. I. Wissenschaftsverlag, Berlin, pp 213–240

    Google Scholar 

  • Duquenne V (1999) Latticial structures in data analysis. Theoretical Computer Science 217(2):407–436

    Google Scholar 

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

    MathSciNet  Google Scholar 

  • Estrada E, Rodríguez-Velázquez JA (2005) Complex networks as hypergraphs. Phys A 364:581–594

    Article  Google Scholar 

  • Forkman B, Haskell MJ (2004) The maintenance of stable dominance hierarchies and the pattern of aggression: support for the suppression hypothesis. Ethology 110:737–744

    Article  Google Scholar 

  • Forsyth E, Katz L (1946) A matrix approach to the analysis of sociometric data: preliminary report. Sociometry 9:340–347

    Article  Google Scholar 

  • Freeman LC (2004) The development of social network analysis: a study in the sociology of science. Empirical Press, Vancouver

    Google Scholar 

  • Freeman LC (2005) Graphical techniques for exploring social network data. In: Carrington PJ, Scott J, Wasserman S (eds) Models and methods in social network analysis. Cambridge University Press, Cambridge, pp 248–269

    Chapter  Google Scholar 

  • Freeman LC, White DR (1993) Using Galois lattices to represent network data. In: Marsden PV (ed) Sociological methodology. Blackwell, Oxford, pp 127–146

    Google Scholar 

  • Hobson JA (1894) The evolution of modern capitalism; a study of machine production. Allen & Unwin/Macmillan, London/New York

    Google Scholar 

  • Höpner M, Krempel L (2003) The politics of the German company network. Working paper 03/9. Max Planck Institute for the Study of Societies, Cologne, Germany

    Google Scholar 

  • Kadushin C (1974) The American intellectual elite. Little, Brown, Boston

    Google Scholar 

  • Kamada T, Kawai S (1989) A general framework for visualizing abstract objects and relations. ACM Trans Graph 10:1–39

    Article  Google Scholar 

  • Kirke DM (1996) Collecting peer data and delineating peer networks in a complete network. Soc Netw 18:333–346

    Article  Google Scholar 

  • Kirke DM (2006) Teenagers and substance use: social networks and peer influence. Palgrave Macmillan, Basingstoke/New York

    Book  Google Scholar 

  • Krackhardt D (1996) Social networks and the liability of newness for managers. In: Cooper CL, Rousseau DM (eds) Trends in organizational behavior, vol 3. Wiley, New York, pp 159–173

    Google Scholar 

  • Krempel L (1999) Visualizing networks with spring embedder: two-mode and valued data. In: Proceedings of the section of statistical graphics. American Statistical Association, Alexandria, pp 36–45

    Google Scholar 

  • Levine JH (1979) Joint-space analysis of ‘pick-any’ data: analysis of choices from an unconstrained set of alternatives. Psychometrika 44:85–92

    Article  Google Scholar 

  • Macfarlane A (1883a) Analysis of relationships of consanguinity and affinity. J R Anthropol Inst G B Irel 12:46–63

    Google Scholar 

  • Macfarlane A (1883b) Appendix to Analysis of relationships of consanguinity and affinity. J R Anthropol Inst G B Irel 12:46–63

    Google Scholar 

  • Mitchell JC (1994) Situational analysis and network analysis. Connections 17:16–22

    Google Scholar 

  • Moody J, McFarland DA, Bender-deMoll S (2005) Visualizing network dynamics. Am J Sociol 110(4):1206–1241

    Article  Google Scholar 

  • Moreno JL (1932) Application of the group method to classification. National Committee on Prisons and Prison Labor, New York

    Google Scholar 

  • Moreno JL (1934) Who shall survive? Nervous and Mental Disease Publishing Company, Washington, DC

    Google Scholar 

  • Morgan LH (1871/1997) Systems of consanguinity and affinity in the human family. University of Nebraska Press, Lincoln

    Google Scholar 

  • Pfeffer J (2017) Visualization of political networks. In: Victor JN, Montgomery AH, Lubell M (eds) The Oxford handbook of political networks, pp 277–300. Oxford University Press, Oxford, UK

    Google Scholar 

  • Pfeffer J, Freeman LC (2015) The historic development of network visualization. In: Sunbelt XXXV conference, Brighton, 23–28 June

    Google Scholar 

  • Richards WD, Seary AJ (2000) Cover illustration. Connections 23:1

    Google Scholar 

  • Richardson DC, Richardson JS (1992) The kinemage – a tool for scientific communication. Protein Sci 1:3–9

    Article  Google Scholar 

  • Roethlisberger FJ, Dickson WJ (1939) Management and the worker. Harvard University Press, Cambridge

    Google Scholar 

  • Sampson SF (1969) A noviate in a period of change: an experimental and case study of relationships. Unpublished PhD dissertation, Department of Sociology, Cornell University

    Google Scholar 

  • Schweitzer VS (1998) Words of power. Coffee Times, Fall

    Google Scholar 

  • Seary AJ (1995) MultiNet for DOS. Presented at International conference on social networks (Sunbelt XV), London

    Google Scholar 

  • Valente TW, Foreman RK, Junge B, Vlahov D (1998) Satellite exchange in the Baltimore needle exchange program. Public Health Rep 113:91–96

    Google Scholar 

  • Warner WL, Lunt PS (1941) The social life of a modern community. Yale University Press, New Haven

    Google Scholar 

  • Weller SC, Romney AK (1990) Metric scaling: correspondence analysis. Sage, Newbury Park

    Book  Google Scholar 

  • White HC, Boorman SA, Breiger RL (1976) Social structure from multiple networks: I. Blockmodels of roles and positions. Am J Sociol 81:730–779

    Article  Google Scholar 

  • Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I (ed) Ordered sets. Reidel, Dordrecht-Boston, pp 445–470

    Chapter  Google Scholar 

  • Wille R (1984) Line diagrams of hierarchical concept systems. Int Classif 11:77–86

    Google Scholar 

  • Windhager F, Mayr E (2012) Cultural Heritage Cube. A conceptual framework for visual exhibition exploration. In: Proceedings of the 16th international conference on information visualisation, pp 540–545. Montpellier, France

    Google Scholar 

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Correspondence to Jürgen Pfeffer .

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Pfeffer, J., Freeman, L.C. (2019). Social Network Visualization, Methods of. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_496-2

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  • DOI: https://doi.org/10.1007/978-3-642-27737-5_496-2

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