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Theories and methods for understanding human social networks

Associate Professor Garry Robins & Prof Pip Pattison (University of Melbourne)
University of Adelaide, 2-6 May 2005




Day 1: Introduction, data and centrality

Session 1
 
0930 -1000 Coffee and registration
1000 -1100 Introduction to social networks [PDF 206kB] (Borgatti & Foster, 2003; Padgett & Ansell 1993)
   
Session 2  
1115 -1300 Exercise: Complete network data collection
  Methods: What is a social network? Representing a network [PDF 623kB]
  Exercise: Egocentric network data collection
  Methods: Social network data collection techniques
  Exercise: Network visualisation using Pajek
   
Session 3  
1400 - 1500 Introduction to essential graph theory concepts [PDF 267kB] (Freeman, 1979)
   
Session 4  
1515 - 1630 Exercise: UCINET: Calculating density, components, geodesics, and centrality; visualising social networks with Netdraw
1630 - 1730 Question time
   

Day 2:  Structure

Session 1  
0930 -1000 Review Day 1
1000 -1100 Structures: Balance, structural holes and the strength of weak ties
[PDF 126kB]
(Burt, Janotta & Mahoney, 1998; Granovetter, 1973)
   
Session 2  
1130 -1230 Methods:  Some definitions of cohesive subsets [PDF 99kB]
  Exercise: UCINET: Cohesive subsets
   
Session 3  
1330 -1430 Conceptualisations of network position  [PDF 191kB] (White, Boorman & Breiger, 1976)
   
Session 4  
1500 -1545 Methods:  Algorithms for network position [PDF 209kB]
1545 -1630 Exercise:  UCINET: structural equivalence and blockmodels
1630 -1730 Question time
   

Day 3: Models for graphs and networks

Session 1  
0930 - 1000 Review Day 2
1000 - 1100 Statistical models: an introduction to random graph distributions [PDF 249kB]
   
Session 2  
1130 - 1200 Stochastic blockmodels [PDF 287kB]
1200 - 1230 Exercise: Stochastic blockmodels: introducing StOCNET
   
Session 3  
1330 - 1430 Small worlds: regularity and randomness [PDF 109 MB]
   
Session 4  
1500 - 1545 Exercise:  Comparing global structures
1545 - 1630 A brief discussion of scale-free degree distributions and of the preferential attachment model [PDF 197kB]
1630 - 1730 Question time
   

Day 4:  Statistical models for social networks: exponential random graph models

Session 1  
0930 - 1000 Review Day 3
1000 - 1100 Markov random graph models [PDF 568kB] (Robins, Pattison, Kalish & Lusher, 2005) (including MCMC ML estimation [PDF 757kB])
   
Session 2  
1130 - 1200 Simulating Markov random graphs [PDF 275kB] (Robins, Pattison & Woolcock, 2005)
1200 - 1230 Exercise: Simulating Markov random graph distributions
   
Session 3  
1330 - 1430 Exponential random graph models:  New specifications [PDF 272kB] (Robins, Snijders, Wang, Handcock & Pattison, 2005)
   
Session 4  
1500 - 1545 Exercise: Fitting exponential random graph models with pnet
1545 - 1630 Modelling multiple networks [PDF 343kB] (Lazega & Pattison, 1999)
   

Day 5: Complex network dependencies: Selection & influence models

Session 1  
0900 - 0930 Review Day 4
0930 - 1030 Selection and influence; Exponential random graph models for social selection [PDF 216kB] (Robins & Pattison, 2005)
   
Session 2  
1100 - 1200 Exercise: Fitting social selection models
   
Session 3  
1230 - 1330 Methods: Network evolution and the co-evolution of networks and behaviour [PDF 282kB] (Snijders, 2001)
   
Session 4  
1345 - 1430 Bipartite graphs and affiliation networks [PDF 281kB]
  Conclusions
   

Reading list

Borgatti, S., & Foster, P. (2003). The network paradigm in organizational research: A review and typology. Journal of Management, 29, 991-1013.
Burt, R. S., Jannotta, J. E. J., & Mahoney, J. T. (1998). Personality correlates of structural holes. Social Networks, 20, 63-87.
Contractor, N., Wasserman, S. & Faust, K. (In press).  Testing multi-theoretical multilevel hypotheses about organizational networks: An analytic framework and empirical example. Academy of Management Journal.
Freeman, L.C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1, 215-239.
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology 78, 1360-1380.
Lazega, E.,& Pattison, P. (1999). Multiplexity, generalized exchange and cooperation in organizations. Social Networks, 21, 67-90.
Nowicki, Krzysztof, & Snijders, T.A.B. (2001).  Estimation and prediction for stochastic blockstructures.  Journal of the American Statistical Association, 96: 1077-1087.
Padgett, J.F., & Ansell, C.K. (1993). Robust action and the rise of the Medici, 1400-1434. American Journal of Sociology, 98, 1259-1319.
Robins, G. L., & Pattison, P. E. (2005).  Interdependencies and social processes: dependence graphs and generalized dependence structures.  In P. Carrington, J. Scott, & S. Wasserman (Eds.), Models and methods in social network analysis.  New York: Cambridge University Press.
Robins, G.L., Pattison, P., Kalish, Y., & Lusher, D. (2005). A workshop on exponential random graph (p*) models for social networks. Social Networks working paper No 1/05: Psychology Department, University of Melbourne.
Robins, G.L., Pattison, P., & Woolcock, J. (2005). Small and other worlds: Global network structures from local processes. American Journal of Sociology.
Robins, G.L., Snijders, T.A.B., & Wang, P. (2005). Recent developments in exponential random graph (p*) models for social networks. Social networks working paper No 2/05: Psychology Department, University of Melbourne.
Shah, P.P. (1998). Who are employees' social referents: Using a network perspective to determine referent others. Academy of Management Journal, 41, 249-268.
Snijders, T.A.B. (2001). The statistical evaluation of social network dynamics. In M.E. Sobel and M.P. Becker (eds.), Sociological Methodology-2001, 361-395. Boston and London: Basil Blackwell.
Wang, P., Robins, G. & Pattison, P. (2005). Pnet user manual. University of Melbourne.
Watts, D., & Strogatz, S. (1998). Collective dynamics of 'small-world' networks.  Nature, 393, 440-442.
White, H.C., Boorman, S.A., & Breiger, R.L. (1976). Social structure from multiple networks: I. Blockmodels of roles and positions. American Journal of Sociology, 87, 517-547.


 

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