Object oriented modeling of social networks

  • Evelien P. H. Zeggelink
  • Reinier Van Oosten
  • Frans N. Stokman
Article

Abstract

The aim of this paper is to explain principles of object oriented modeling in the scope of modeling dynamic social networks. As such, the approach of object oriented modeling is advocated within the field of organizational research that focuses on networks.

We provide a brief introduction into the field of social networks and present an overview of existing network models and methods. Subsequently we introduce an elementary problem field in the social sciences in general, and in studies of organizational change and design in particular: the micro-macro link. We argue that the most appropriate way to hadle this problem is the principle of methodological individualism. For social network analysis, to contribute to this theoretical perspective, it should include an individual choice mechanism and become more dynamically oriented. Subsequently, object oriented modeling is advocated as a tool to meet these requirements for social network analysis. We show that characteristics of social systems that are emphasized in the methodological individualistic approach have their direct equivalences in object oriented models. The link between the micro level where actors act, and the macro level where phenomena occur as a consequence and cause of these actions, can be modelled in a straightforward way.

Keywords

social networks objected oriented modeling dynamics 
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References

  1. AbelsonR. P. and A.Bernstein (1963), “A Computer Model of Community Referendum Controversies,” Public Opinion Quarterly 27, 93–122.Google Scholar
  2. AlbaR.D. (1973), “A Graph Theoretic Definition of a Sociometric Clique,” Journal of Mathematical Sociology 3, 113–126.Google Scholar
  3. AllanG. (1990), Friendship: Developing a Sociological Perspective. New York: Harvester.Google Scholar
  4. AndersonC.J., S.S.Wasserman and K.Faust (1992), “Building Stochastic Blockmodels,” Social Networks 14, 137–161.Google Scholar
  5. AnthonisseJ.M. (1971), The Rush in a Directed Graph. Amsterdam: Mathematical Centre.Google Scholar
  6. BaerveldtC. and T.A.B.Snijders (1994), “Influences on and from the Segmentation of Networks: Hypotheses and Tests,” Social Networks 16, 213–232.Google Scholar
  7. BanksD.L. and K.M.Carley (1996), “Models for Network Evolution,” Journal of Mathematical Sociology 21, 173–196.Google Scholar
  8. Barnes J.A. (1979), “Network Analysis: Orienting Notion, Rigorous Technique or Substantive Field of Study,” in P.W.Holland and S.Leinhardt (Eds.) Perspectives on Social Network Research, New York: Academic Press.Google Scholar
  9. BartholomewD.J. (1967), Stochastic Models for Social Processes. New York: Wiley.Google Scholar
  10. BavelasA. (1950), “Communication Patterns in Task Oriented Groups,” Journal of the Acoustical Society of America 22, 271–288.Google Scholar
  11. BeauchampM.A. (1965), “An Improved Index of Centrality,” Behavioral Science 10, 161–163.Google Scholar
  12. BerkowitzS.D. (1982), An Introduction to Structural Analysis: the Network Approach to Social Research. Toronto: Butterworths.Google Scholar
  13. BlumT.C. (1985), “Structural Constraints on Interpersonal Relationships: A Test of Blau's Macrosociological Theory,” American Journal of Sociology 91, 511–521.Google Scholar
  14. BonacichP. (1987), “Power and Centrality; A Family of Measures,” American Journal of Sociology 92, 1170–1182.Google Scholar
  15. BorgattiS.P., M.G.Everett and P.R.Shirey (1990), “LS Sets, Lambda Sets and Other Cohesive Subsets,” Social Networks 12, 337–357.Google Scholar
  16. BoudonR. and F.Bourricaud (1982), Dictionnaire Critique de la Sociologie, Paris: Presses Universitaires de France.Google Scholar
  17. BoydJ.P. (1991), Social Semigroups: A Unified Theory of Scaling and Blockmodeling as Applied to Social Networks, Fairfax, VA: George Mason University Press.Google Scholar
  18. BurtR. (1982), Toward a Structural Theory of action: Network Models of Social Strucgure, Perception, and Action. New York: Academic Press.Google Scholar
  19. BurtR. (1992), Structural Holes. The Social Structure of Competition. Cambridge, MA: Harvard University Press.Google Scholar
  20. Carley K. (1989), “The Value of Cognitive Foundations for Dynamic Social Theory,” Journal of Mathematical Sociology 14, 171–208.Google Scholar
  21. CarleyK. (1990), “Group Stability: A Socio-Cognitive Approach,” Advances in Group Processes 7, 1–44.Google Scholar
  22. CarleyK. (1991a), “A Theory of Group Stability,” American Sociological Review 56, 331–354.Google Scholar
  23. CarleyK. (1991b), “Growing Up: The Development and Acquisition of Social Knowledge,” in J.A.Howard and P.L.Callero (Eds.) The Self-Society Dynamic: Cognition, Emotion, and Action, Cambridge, MA: Cambridge University Press.Google Scholar
  24. Carley K.M. and M.J. Prietula (1994), “ACTS Theory: Extending the Model of Bounded Rationality,” in K.M.Carley and M.J.Prietula (Eds.) Computational Organization Theory, Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  25. CartwrightD. and F.Harary (1956), “Structural Balance: A Generalization of Heider's Theory,” Psychological Review 63, 277–293.Google Scholar
  26. Coleman J.S. (1964), Introduction to Mathematical Sociology. New York: Free Press of Glencoe.Google Scholar
  27. Coleman J.S. (1986), “Micro Foundations and Macrosocial Theory,” in S.Lindenberg, J.S.Coleman and S.Nowak (Eds.), Approaches to Social Theory, New York: Russell Sage Foundation.Google Scholar
  28. Coleman J.S. (1990), Foundations of Social Theory, Cambridge, MA: Harvard University Press.Google Scholar
  29. DavisJ.A. (1963), “Structural Balance, Mechanical Solidarity, and Interpersonal Relations,” American Journal of Sociology 68, 444–463.Google Scholar
  30. DavisJ.A. (1967), “Clustering and Structural Balance in Graphs,” Human relations 20, 181–187.Google Scholar
  31. DavisJ.A. and S.Leinhardt (1972), “The Structure of Positive Interpersonal Relations in Small Groups,” in J.Berger (Ed.) Sociological Theories in Progress, vol. 2, Boston: Houghton-Mifflin.Google Scholar
  32. DawkinsR. (1987), The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design. New York: Norton.Google Scholar
  33. DeVosH. and E.P.H.Zeggelink (1994), “The Emergence of Reciprocal Altruism and Group Living: An Object Oriented Simulation Model of Human Social Evolution,” Social Science Information 33, 493–517.CrossRefMATHGoogle Scholar
  34. Doreian P.D. (1979), “Structural Control Models of Group Processes,” in P.W.Holland and S.Leinhardt (Eds.) Perspectives on Social Network Research, New York: Academic Press.Google Scholar
  35. DoreianP., R.Kapuscincki, D.Krackhardt and J.Szcypula (1996), “A Brief History of Balance Through Time,” Journal of Mathematical Sociology 21, 113–131.Google Scholar
  36. FararoT.J. and J.Skvoretz (1984), “Biased Networks and Social Structure Theorems, Part II.” Social Networks 6, 223–258.Google Scholar
  37. FaustK. (1988), “Comparison of Methods for Positional Analysis: Structural and General Equivalence,” Social Networks 10, 313–342.Google Scholar
  38. FaustK. and S.S.Wasserman (1992), “Blockmodels: Interpretation and Evaluation,” Social Networks 14 5–61.Google Scholar
  39. FestingerL. (1950), “Informal Social Communication,” Psychological Review 57, 271–282.Google Scholar
  40. Fiksel J. (1980), “Dynamic Evolution in Societal Networks,” Journal of Mathematical Sociology 7, 27–46.Google Scholar
  41. FischerC.S. (1982), To Dwell Among Friends: Personal Networks in Town and City, Chicago: University of Chicago Press.Google Scholar
  42. FienbergS.E. and S.S.Wasserman (1981), “Categorical Data Analysis of Simple Sociometric Relations” in S.Leinhardt (Ed.) Sociological Methodology, San Francisco: Jossey-Bass.Google Scholar
  43. FrankK.A. (1995), “Identifying Cohesive Subgroups,” Social Networks 17, 27–56.Google Scholar
  44. FrankO. (1991), “Statistical Analysis of Change in Networks,” Statistica Neerlandica 45, 283–293.Google Scholar
  45. Freeman L.C. (1979), “Centrality in Social Networks: Conceptual Clarification,” Social Networks 1, 215–239.Google Scholar
  46. FreemanL.C. (1992), “The Sociological Concept of ‘Group”: An Empirical Test of Two Models,” American Journal of Sociology 98, 152–166.Google Scholar
  47. FreemanL.C., S.P.Borgatti, and D.White (1991), “Centrality in Valued Graphs: A Measure of betweenness based on Network Flow,” Social Networks 13, 141–154.Google Scholar
  48. FreemanL.C., D.R.White and A.K.Romney (Eds.) (1989), Research Methods in Social Network Analysis, Fair-fax, VA: George Mason University Press.Google Scholar
  49. FrenchJ.R. (1956), “A Formal Theory of Social Power,” Psychological review 63, 181–194.Google Scholar
  50. GoldbergA. and D.Robson (1983), Smaltalk-80. The Language and its Implementation. Reading, MA: Addison-Wesley.Google Scholar
  51. HageP. and F.Harary (1995), “Eccentricity and Centrality in Networks,” Social Networks 17, 57–63.Google Scholar
  52. HallinanM.T. (1974), The Structure of Positive Sentiment. New York: Elsevier.Google Scholar
  53. HallinanM.T. (1979), “The Process of Friendship Formation,” Social Networks 1, 93–210.Google Scholar
  54. HararyF. (1969), Graph Theory. Reading, MA: Addison-Wesley.Google Scholar
  55. HararyF., R.Z.Norman and M.Cartwright (1965), Structural Models: An Introduction to the Theory of Directed Graphs. New York: Wiley.Google Scholar
  56. HeiderF. (1958), The Psychology of Interpersonal Relations. New York: Wiley.Google Scholar
  57. Hoede, C. (1978), “A New Status Score for Actors in a Social Network,” Twente University, Department of Applied Mathematics.Google Scholar
  58. HoivikT. and N.P.Gleditsch (1970), “Structural Parameters of Graphs; A Theoretical Investigation,” Quality and Quantity 4, 193–209.Google Scholar
  59. HollandP.W. and S.Leinhardt (1970), “A Method for Detecting Structure in Sociometric Data,” American Journal of Sociology 70, 492–573.Google Scholar
  60. HollandP.W. and S.Leinhardt (1971), “Transitivity in Structural Models of Small Groups,” Comparative group studies 2, 107–124.Google Scholar
  61. HollandP.W. and S.Leinhardt (1972), “Some Evidence on the Transitivity of Positive Interpersonal Sentiment,” American Journal of Sociology 72, 1205–1209.Google Scholar
  62. HollandP.W. and S.Leinhardt (1976), “Local Structure in Social Networks,” in D.Heise (Ed.), Sociological Methodology, San Francisco: Jossey Bass.Google Scholar
  63. HollandP.W. and S.Leinhardt (1977a), “A Dynamic Model for Social Networks,” Journal of Mathematical Sociology 5, 5–20.Google Scholar
  64. HollandP.W. and S.Leinhardt (1977b), “Social Structure as a Network Process,” Zeitschrift für Soziologie 6, 386–402.Google Scholar
  65. HollandP.W. and S.Leinhardt (1979), Perspectives on Social Network Research. New York: Academic Press.Google Scholar
  66. HollandP.W. and S.Leinhardt (1981), “An Exponential Family of Probability Distributions for Directed Graphs,” Journal of the American Statistical Association 76, 33–50.Google Scholar
  67. HubbellC.H. (1965), “An Input-Output Approach to Clique Identification,” Sociometry 28, 377–399.Google Scholar
  68. Hummel, H.J. and W. Sodeur (1984), Strukturentwicklung unter Studienanfangern. Ein Werkstattbericht, Universitat Duisburg.Google Scholar
  69. Hummel H.J. and W. Sodeur (1990), “Evaluating Models of Change in Triadic Sociometric Structures,” in J.Weesie and H.Flap (Eds.) Social networks through time, Utrecht: ISOR.Google Scholar
  70. HummonN.P. and T.J.Fararo (1995), “Actors and Networks as Object,” Social Networks 17, 1–20.Google Scholar
  71. Hunter J.E. (1978), “Dynamic Sociometry,” Journal of Mathematical Sociology 6, 87–138.Google Scholar
  72. Hunter J.E. (1979), “Toward a General Framework for Dynamic Theories of Sentiment in Small Groups Derived from Theories of Attitude Change,” in P.W.Holland and S.Leinhardt (Eds.) Perspectives on Social Network Research, New York: Academic Press.Google Scholar
  73. JohnsenE.C. (1986), “Structure and Process: Sgreement Models for Friendship Formation,” Social Networks 8, 257–306.Google Scholar
  74. JohnsenE.C. (1989), “The Micro-Macro Connection: Exact Structure and Process,” in F.Roberts (Ed.) Applications of Combinatorics and Graph Theory to the Biological and Social Sciences. New York: Springer Verlag.Google Scholar
  75. KatzL. (1953), “A New Status Index Derived from Sociometric Data Analysis,” Psychometrika 18, 39–43.Google Scholar
  76. KatzL. and C.H.Proctor (1959), “The Concept of Configuration of Interpersonal Relations in a Group as a Time Dependent Stochastic Process,” Psychometrika 24, 317–327.Google Scholar
  77. KemenyJ.G., and J.L.Snell (1962), Mathematical Models in the Social Sciences, Waltham, MA: Blaisdell.Google Scholar
  78. KillworthP.D. and H.R.Bernard (1976), “A Model of Human Group Dynamics,” Social Science Research 5, 173–224.Google Scholar
  79. KnokeD. and J. H.Kuklinski (1982), Network Analysis: Quantitative Applications in the Social Sciences No. 28, London: Sage.Google Scholar
  80. KrempelL. (1987), Soziale Interaktionen: Einstellungen, Biographien, Situationen und Beziehungsnetzwerke; Dynamische Ereignisanalysen. Bochum: Ulrich Schallwig Verlag.Google Scholar
  81. Krempel, L. (1988), “Interpersonal Structure and Contact: Empirical Evidence from the Analysis of a Series of Social Networks in Time and Contact as a Process. An Analysis with Tools of ‘Event History’ Analysis,” Unpublished manuscript.Google Scholar
  82. Lazega, E. and M. van Duijn (1996), “Formal Structure and Exchanges of Advice in a Law Firm: A Random Effects Model,” forthcoming.Google Scholar
  83. LeavittH.J. (1951), “Some Effects on Communication Patterns on Group Performance,” Journal of Abnormal and Social Psychology 46, 38–50.Google Scholar
  84. LeendersR.T.A.J. (1995), Structure and Influence: Statistical Models for the Dynamics of Actor Attributes, Network Structure and Their Interdepenence. Amsterdam: Thesis.Google Scholar
  85. LeendersR.T.A.J. (1996), “Dynamics of Friendship and Best Friendship Choices,” Journal of Mathematical Sociology 21, 133–148.Google Scholar
  86. Lehermann Madsen O. and B. Moller-Pedersen (1988), “What Object-Oriented Programming May Be—and What It Does Not Have To Be,” in S.Giessing and K.Nygaard (Eds.) ECOOP 88. European Conference on Object-Oriented Programming, Berlin: Springer Verlag.Google Scholar
  87. Levitt R.E., G.P. Cohen, J.C. Kunz, C.I. Nass, T. Christianse, and Y. Jin (1994), “The ‘Virtual Design Team’: Simulating How Organization Structure and Information Processing Tools Affect Team Performance,” in K.M.Carley and M.J.Prietula (Eds.) Computational Organization Theory, Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  88. LindenbergS. (1985), “An Assessment of the New Political Economy: Its Potential for the Social Sciences and for Sociology in Particular,” Sociological Theory 3, 99–114.Google Scholar
  89. LindenbergS. (1990), “Homo Socio-Economicus: The Emergence of a General Model of Man in the Social Sciences,” Journal of Institutional and Theoretical Economics (JITE) 146, 727–748.Google Scholar
  90. LorrainF., and H.C.White (1971), “Structural Equivalence of Individuals in Social Networks,” Journal of Mathematical Sociology 1, 49–80.Google Scholar
  91. LuceR.D. and A.Perry (1949), “A Method of Matrix Analysis of Group Structure,” Psychometrika 14, 94–116.Google Scholar
  92. MasuchM. and P.LaPotin (1989), “Beyond Garbage Cans: An AI Model of Organizational Choice,” Administrative Science Quarterly 34, 38–67.Google Scholar
  93. MayerT.F. (1984), “Parties and Networks: Stochastic Models for Relationship Networks,” Journal of Mathematical Sociology 10, 51–103.Google Scholar
  94. MitchellJ.C. (1969), Social Network in Urban Situations. Manchester: Manchester University Press.Google Scholar
  95. MokkenR.J. (1979), “Cliques, Clubs and Clans,” Quality and Quantity 13, 161–173.PubMedGoogle Scholar
  96. MullinM. (1989), Object Oriented Program Design with Examples in C ++. Reading, MA: Addison-Wesley.Google Scholar
  97. Nohria N. and R.G. Eccles (1992), (Eds.) Networks and Organizations. Boston: Harvard Business School Press.Google Scholar
  98. Objectworks (1989), Smalltalk-80 User's Guide, Parc Place Systems.Google Scholar
  99. Objectworks (1990), Smalltalk Release 4, User's Guide, Parc Place Systems.Google Scholar
  100. PattisonP.E. (1988), “Network Models: Some Comments on Papers in This Special Issue,” Social Networks 10, 383–412.Google Scholar
  101. PattisonP.E. (1993), Algebraic Models for Social Networks. England: Cambridge University Press.Google Scholar
  102. PattisonP.E. and S.S.Wasserman (1995), “Constructing Algebraic Models for Local Social Networks Using Statistical Methods,” Journal of Mathematical Psychology 39: 57–72.Google Scholar
  103. PinsonL.J. and R.S.Wiener (1988), An Introduction to Object-Oriented Programming and Smalltalk, Reading, MA: Addison-Wesley.Google Scholar
  104. Popping R. (1989), “The Distance Matrix and Distance-Based Measures,” in C.J.A.Sprenger and F.N.Stokman (Eds.) GRADAP; Graph Definition and Analysis Package, Groningen, the Netherlands: ProGAMMA.Google Scholar
  105. Rainio K. (1966), “A Study on Sociometric Group Structure: An Application of a Stochastic Theory of Social Interaction,” in J.Berger, M.Zelditch and B.Anderson (Eds.) Sociological theories in progress, Boston: Houghton Mifflin.Google Scholar
  106. Rumelhart D. E. and J. L. McClelland (Eds.) (1988), Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises. Cambridge, MA: MIT Press.Google Scholar
  107. RungerG. and S. S.Wasserman (1979), “Longitudinal Analysis of Friendship Networks,” Social Networks 2, 143–154.Google Scholar
  108. ScottJ. (1991), Social Network Analysis; A Handbook. London: Sage.Google Scholar
  109. SeidmanS.B. (1983), “LS Sets and Cohesive Subsets of Graphs and Hypergraphs,” Social Networks 5, 92–96.CrossRefGoogle Scholar
  110. SeidmanS.B. and B.L.Foster (1978), “A Graph Theoretic Generalization of the Clique Concept,” Journal of Mathematical Sociology 6, 139–154.Google Scholar
  111. SimonH.A. (1957), Models of Man. New York: Wiley.Google Scholar
  112. SkvoretzJ. (1991), “Theoretical and Methodological Models of Networks and Relations,” Social Networks 13, 275–300.Google Scholar
  113. SkvoretzJ., K.Faust, and T.J.Fararo (1996), “Social Structure, Networks, and E-State Structuralism Models,” Journal of Mathematical Sociology 21, 57–76.Google Scholar
  114. SnijdersT.A.B. (1981), “The Degree Variance: An Index of Graph Heterogeneity,” Social Networks 3, 163–174.Google Scholar
  115. SnijdersT.A.B. (1990), “Testing for Change in a Digraph at Two Time Ooints,” Social Networks 12, 359–373.Google Scholar
  116. SnijdersT.A.B. (1991), “Enumeration and Simulation Methods For 0–1 Matrices with Given Marginals,” Psychometrika 56, 397–417.Google Scholar
  117. SnijdersT.A.B. (1996), “Stochastic Actor-Oriented Models for Network Change,” Journal of Mathematical Sociology 21, 149–172.Google Scholar
  118. SnijdersT.A.B. and K.Nowicki (1994), “Estimation and Prediction for Stochastic Block Models for Graphs with Latent Block Structure,” internal publication, Heymans Bulletins 93: 1–26.Google Scholar
  119. SnijdersT.A.B. and F.N.Stokman (1987), “Extensions of Triad Counts to Networks with Different Subsets of Points and Testing Underlying Random Graph Distributions,” Social Networks 9, 249–275.Google Scholar
  120. SörensenA.B. and M.T.Hallinan (1976), “A Stochastic Model for Change in Group Structure,” Social Science Research 5, 43–61.Google Scholar
  121. SprengerC.J.A. and F.N.Stokman (1989), GRADAP User's Manual, Groningen: ProGAMMA.Google Scholar
  122. Stokman F.N. and P. Doreian (1996), “Evolution of Social Networks: Processes and Principles,” in P.Doreian and F.N.Stokman (Eds.) Evolution Of Social Networks, Langhorne, PA: Gordon and Breach, forthcoming.Google Scholar
  123. Stokman F.N. and J.M.M. Van den Bos (1992), “A Two-Stage Model of Policy Making, With an Empirical Test in the US Energy Policy Domain,” in G.Moore and J.Allen Whitt (Eds.) The Political Consequences of Social Networks, Volume 4 of Research and Society, Greenwich, CT: JAI Press.Google Scholar
  124. Stokman, F.N. and R. Van Oosten (1994), “Generic Steps in Collective Decision Making,” Paper presented at the Sunbelt XIV International Social Network Conference, New Orleans, Louisiana, February 17–20.Google Scholar
  125. Stokman F.N. and E.P.H. Zeggelink (1996a), “Is Politics Power or Policy Oriented? A Comparative Analysis of Dynamic Access Models in Policy Networks,” Journal of Mathematical Sociology 21, 77–111.Google Scholar
  126. Stokman F.N. and E.P.H. Zeggelink (1996b), “‘Self-Organizing’ Friendship Networks,” in W.B.G.Liebrand and D.M.Messick (Eds.) Frontiers in Social Dilemmas Research. Berlin: Springer-Verlag.Google Scholar
  127. StraussD. and M.Ikeda (1990), “Pseudolikelihood Estimation for Social Networks,” Journal of the American Statistical Association 85, 204–212.Google Scholar
  128. TaylorM. (1969), “Influence Structures,” Sociometry 32, 490–502.Google Scholar
  129. Van Duijn M.A.J. (1995), “Estimation of Random Effect Models for Directed Graphs,” in T.A.B.Snijders, B.Engel, J.C.vanHouwelingen, A.Keen, G.J.Stemerdink, and M.Verbeek (Eds.) Toeval zit overal; Symposium Statistische Software, nr 7, Groningen: ProGAMMA.Google Scholar
  130. Van Roozendaal, P. and E.P.H. Zeggelink (1996), “Coalition Formation in Political Networks: A Simulation Approach,” forthcoming.Google Scholar
  131. Verkama M., R.P. Hämäläinen, and H. Ehtamo (1994), “Modeling and Computational Analysis of Reactive Behavior in Organizations,” in K.M.Carley and M.J.Prietula (Eds.) Computational Organization Theory, Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  132. Visual Works 2.5 (1995), Visual Works 2.5. User's Guide, Parc Place Systems.Google Scholar
  133. WassermanS.S. (1978), “Models for Binary Directed Graphs and Their Applications,” Advances in Applied Probability 10, 803–818.Google Scholar
  134. WassermanS.S. (1980a), “Analyzing Social Networks as Stochastic Processes,” Journal of the American Statistical Association 75, 280–294.Google Scholar
  135. WassermanS.S. (1980b), “A Stochastic Model for Directed Graphs with Transition Rates Determined by Reciprocity,” in K.Schuessler (Ed.), Sociological Methodology, San Francisco: Jossey Bass.Google Scholar
  136. WassermanS.S. (1987), “Conformity of Two Sociometric Relations,” Psychometrika 52, 3–18.Google Scholar
  137. WassermanS.S. and K.Faust (1994), Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press.Google Scholar
  138. WassermanS.S. and J.Galaskiewicz (1994), Advances in Social Network Analysis: Research From the Social and Behavioral Sciences. Newbury Park, CA: Sage.Google Scholar
  139. WassermanS.S. and D.Iacobucci (1988), “Sequential Social Network Data,” Psychometrika 53, 261–282.PubMedGoogle Scholar
  140. WassermanS.S. and S.O.Weaver (1985), “Statistical Analysis of Binary Relational Data: Parameter Estimation,” Journal of Mathematical and Statistical Psychology 29, 406–427.Google Scholar
  141. Weesie J. and H. Flap (Eds.) (1990), Social Networks Through Time. Utrecht, the Netherlands: ISOR.Google Scholar
  142. Wellman B. and S.D. Berkowitz (Eds) (1988), Social Structures: A Network Approach. Cambridge: Cambridge University Press.Google Scholar
  143. WellmanB., O.Frank, V.Espinoza, S.Lundquist, and C.Wilson (1991), “Integrating Individual, Relational and Structural Analysis,” Social Networks 13, 223–249.Google Scholar
  144. WhiteD.R. and S.P.Borgatti (1994), “Betweenness Centrality Measures for Directed Graphs,” Social Networks 16, 335–346.Google Scholar
  145. WhiteH.C., S.A.Boorman and R.L.Breiger (1976), “Social Structure from Multiple Networks I: Blockmodels of Roles and Positions,” American Journal of Sociology 81, 730–779.Google Scholar
  146. WipplerR. (1978), “The Structural-Individualistic Approach in Dutch Sociology: Toward an Explanatory Social Science,” The Netherlands Journal of Sociology 14, 135–155.Google Scholar
  147. WongG.Y. (1987), “Bayesian Models for Directed Graphs,” Journal of the American Statistical Association 82, 140–148.Google Scholar
  148. WrightsmanL.S. and K.Deaux (1981), Social Psychology in the Eighties. 3rd. Monterey, CA: Brooks/Cole.Google Scholar
  149. ZeggelinkE.P.H. (1993), Strangers Into Friends; The Evolution of Friendship Networks Using an Individual Oriented Modeling Approach. Amsterdam: Thesis Publishers.Google Scholar
  150. ZeggelinkE.P.H. (1994), “Dynamics of Structure: An Object-Oriented Approach,” Social Networks 16, 295–333.Google Scholar
  151. ZeggelinkE.P.H. (1995), “Evolving Friendship Networks: An Individual Oriented Approach Implementing Similarity,” Social Networks 17, 83–110.Google Scholar

Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Evelien P. H. Zeggelink
    • 1
  • Reinier Van Oosten
    • 1
  • Frans N. Stokman
    • 1
  1. 1.Interuniversity Center for Social Science Theory and Methodology (ICS)University of GroningenThe Netherlands

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