Applying SIENA
Abstract
We give a nontechnical introduction into recently developed methods for analyzing the coevolution of social networks and behavior(s) of the network actors. This coevolution is crucial for a variety of research topics that currently receive a lot of attention, such as the role of peer groups in adolescent development. A family of dynamic actor-driven models for the coevolution process is sketched, and it is shown how to use the SIENA software for estimating these models. We illustrate the method by analyzing the coevolution of friendship networks, taste in music, and alcohol consumption of teenagers.
References
Baerveldt C. , Snijders T. A. B. (1994). Influences on and from the segmentation of networks: Hypotheses and tests. Social Networks, 16, 213– 232Boer P. , Huisman M. E. , Snijders T. A. B. , Zeggelink E. P. H. (2003). StOCNET: An Open Software System for the Advanced Statistical Analysis of Social Networks (Version 1.4) [Computer software]. Groningen, the Netherlands: ProGAMMA/ICS, University of Groningen. Retrieved November 05, 2005, from stat.gamma.rug.nl/stocnet/Bourdieu P. (1984). Distinction: A social critique of the judgement of taste . London: Routledge [|amp|] KeganBryson B (1996). Anything but heavy metal: Symbolic exclusion and musical dislikes. American Sociological Review, 61, 884– 899Bush H. , West P. , Michell L. (1997). The role of friendship groups in the uptake and maintenance of smoking amongst pre-adolescent and adolescent children: Distribution of frequencies (Working Paper No. 62 of the Medical Sociology Unit). Glasgow, Scotland: Medical Research CouncilCarley K (1991). A theory of group stability. American Sociological Review, 56, 331– 354Carrington P. , Scott J. , Wasserman S. (Eds.) (2005). Models and methods in social network analysis . New York: Cambridge University PressDoreian P. (1990). Network autocorrelation models: Problems and prospects. In D. A. Griffith (Ed.) Spatial statistics: Past, present, future (pp 369-389). Ann Arbor: Michigan Document ServicesDorogovtsev S. N. , Goltsev A. V. , Mendes J. F. F. (2002). Ising model on networks with an arbitrary distribution of connections. Physical Review E, 66, 016104l 1– 5Friedkin N. (1998). A structural theory of social influence . Cambridge: Cambridge University PressHogg M. A. , Abrams D. , Otten S. , Hinkle S. (2004). The social identity perspective. Intergroup relations, self-conception, and small groups. Small Group Research, 35, 246– 276Holland P. W. , Leinhardt S. (1973). The structural implications of measurement error in sociometry. Journal of Mathematical Sociology, 3, 85– 111Huisman M. E. , Snijders T. A. B. (2003). Statistical analysis of longitudinal network data with changing composition.. Sociological Methods [|amp|] Research, 32, 253– 287Katz-Gerro T. (1999). Cultural consumption and social stratification: Leisure activities, musical tastes, and social location.. Sociological Perspectives, 42, 627– 646Koskinen J. (2004). Essays on Bayesian inference for social networks . Unpublished doctoral dissertation, Stockholm University, Stockholm, SwedenLatané B. , Nowak A. (1997). Self-organizing social systems: Necessary and sufficient conditions for the emergence of clustering, consolidation and continuing diversity.. Progress in Communication Science, 13, 43– 74Macy M. W. , Kitts J. , Flache A. , Benard S. (2003). Polarization in dynamic networks: A Hopfield model of emergent structure.. In R. Breiger, K. Carley, P. Pattison (Eds.) Dynamic social network modelling and analysis: Workshop summary and papers (pp. 162-173). Washington, DC: National Academies PressMark N. (1998). Beyond individual differences: Social differentiation from first principles. American Sociological Review, 63, 309– 330McPherson J. M. , Smith-Lovin L. , Cook J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415– 444Michell L. , Amos A. (1997). Girls, pecking order and smoking.. Social Science [|amp|] Medicine, 44, 1861– 1869Michell L. , West P. (1996). Peer pressure to smoke: The meaning depends on the method.. Health Education Research Theory [|amp|] Practice, 11, 39– 49Molenaar I. M. , Sijtsma K. , Boer P. (2000). MSP5 for Windows. A Program for Mokken Scale Analysis for Polytomous Items (Version 5.0) [Computer software]. Groningen, the Netherlands: iec ProGAMMAPearson M. , West P. (2003). Social network analysis and Markov processes in a longitudinal study of friendship groups and risk-taking. Connections, 25, 59– 76Roe K. (1985). Swedish youth and music: Listening patterns and motivations.. Communication Research, 12, 353– 362Roe K. (1996). Music and identity among European youth: Music as communication. In P. Rutten (Ed.), Music in Europe: Part 2. Music, culture and society in Europe (pp. 85-97). Brussels, Belgium: European Music OfficeSimmel G. (1904). Fashion. International Quarterly, 10, 130– 155Snijders T. A. B. (1996). Stochastic actor-oriented models for network change. Journal of Mathematical Sociology, 21, 149– 176Snijders T. A. B. (2001). The statistical evaluation of social network dynamics. In M. E. Sobel, M. P. Becker (Eds.), Sociological methodology—2001 (pp. 361-395). Boston and London: Basil BlackwellSnijders T. A. B. (2005). Models for longitudinal network data. In P. Carrington, J. Scott, S. Wasserman (Eds.), Models and methods in social network analysis (pp. 215-247). New York: Cambridge University PressSnijders T. A. B. , Steglich C. , Schweinberger M. (in press) Modeling the co-evolution of networks and behavior. In K. van Montfort, H. Oud, A. Satorra (Eds.), Longitudinal models in the behavioral and related sciences. Mahwah, NJ: Lawrence ErlbaumSnijders T. A. B. , Steglich C. , Schweinberger M. , Huisman M. (2005). SIENA version 2.1 [Computer software and manual]. Groningen, the Netherlands: ICS / Department of Sociology, University of Groningen. Retrieved (February 21, 2005). from http://stat.gamma.rug.nl/stocnet.Snijders T. A. B. , van Duijn M. A. J. (1997). Simulation for statistical inference in dynamic network models.. In R. Conte, R. Hegselmann, P. Terna (Eds.), Simulating social phenomena (pp. 493-512). Berlin: SpringerSteglich C. , Snijders T. A. B. , Pearson M. (2004). Dynamic networks and behavior: Separating selection from influence. Manuscript submitted for publicationSuzuki T. , Best J. (2003). The emergence of trendsetters for fashions and fads: Kogaru in 1990s Japan. Sociological Quarterly, 44, 61– 79van de Bunt G. G. , van Duijn M. A. J. , Snijders T. A. B. (1999). Friendship networks through time: An actor-oriented statistical network model. Computational [|amp|] Mathematical Organization Theory, 5, 167– 192Veblen T. (1899). The theory of the leisure class . New York: Macmillan