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View all- CHEN HGOLDBERG MMAGDON-ISMAIL MWALLACE W(2008)REVERSE ENGINEERING A SOCIAL AGENT-BASED HIDDEN MARKOV MODEL — ViSAGEInternational Journal of Neural Systems10.1142/S012906570800175018:06(491-526)Online publication date: Dec-2008
ViSAGE: A Virtual Laboratory for Simulation and Analysis of Social Group Evolution
Authors: 
Jeffrey Baumes, Hung-Ching (Justin) Chen, Matthew Francisco, Mark Goldberg, Malik Magdon-Ismail, William WallaceAuthors Info & Claims
Article No.: 8, Pages 1 - 35
Abstract
We present a modeling laboratory, Virtual Laboratory for the Simulation and Analysis of Social Group Evolution (ViSAGE), that views the organization of human communities and the experience of individuals in a community as contingent upon on the dynamic properties, or micro-laws, of social groups. The laboratory facilitates the theorization and validation of these properties through an iterative research processes that involves (1) forward simulation experiments, which are used to formalize dynamic group properties, (2) reverse engineering from real data on how the parameters are distributed among individual actors in the community, and (3) grounded research, such as participant observation, that follows specific activities of real actors in a community and determines if, or how well, the micro-laws describe the way choices are made in real world, local settings. In this article we report on the design of ViSAGE. We first give some background to the model. Next we detail each component. We then describe a set of simulation experiments that we used to further design and clarify ViSAGE as a tool for studying emergent properties/phenomena in social networks.
References
[1]
Adamic, L. and Ader, E. 2003. Friends and neighbours on the web. Social Netw., 211--230.
[2]
Backstrom, L., Huttenlocher, D., Kleinberg, J., and Lan, X. 2006. Group formation in large social networks: Membership, growth, and evolution. In ACM International Conference on Knowledge Discovery and Data Mining. 44--54.
[3]
Billari, F., Fent, T., Prskawetz, A., and Scheffran, J., Eds. 2006. Agent-Based Computational Modelling: Applications in Demography, Social, Economic and Environmental Sciences. Physica-Verlag Heidelberg.
[4]
Bloor, D. 1999. Anti-latour. Studies Hist. Philos. Sci. 30, 1, 80--112.
[5]
Borgatti, S. P., Jones, C., and Everett, M. G. 1998. Network measures of social capital. Connections 21, 2, 10.
[6]
Burt, R. S. 1992. Structural Holes: The Social Structure of Competition. Harvard University Press, Cambridge, MA.
[7]
Butler, B. S. 1999. The Dynamics of cyberspace: Examining and modelling online social structures. Ph.D. dissertation, Carnegie Mellon University.
[8]
Byrne, D. 2002. Interpreting Quantitative Data. Sage Publications, Thousand Oaks, CA.
[9]
Chattoe, E. 2002. Review: computational techniques for modelling learning in economics. J. Artif. Soc. Social Simul. 5, 1.
[10]
Collins, R. 1994. Why the social sciences won't become high-consensus, rapid-discovery science. Sociol. Forum 9, 2, 155--177.
[11]
Diwan, R. 2000. Relational wealth and the quality of life. J. Socio-Econ. 29, 305--340.
[12]
Epstein, J. M. 1999. Agent-based computational models and generative social science. Complexity 4, 5, 41--60.
[13]
Epstein, J. M. and Axtell, R. 1996. Growing Artifical Societies: Social Science From the Bottom Up. Brookings Institution Press.
[14]
Freeman, L. C. 2004. The Development of Social Network Analysis: A Study in the Sociology of Science. Empirical Press, Vancouver.
[15]
Getoor, L., Friedman, N., Koller, D., and Taskar, B. 2003. Learning probabilistic models of link structure. J. Mach. Learn. Res., 679--707.
[16]
Giddens, A. 1984. The Constitution of Society: Outline of the Theory of Structuration. University of California Press, Berkeley.
[17]
Glasser, B. and Strauss, A. 1967. The Discovery of Grounded Theory: Strategies for Qualitative Reserach. Aldine Publishing Company.
[18]
Goldberg, M., Horn, P., Magdon-Ismail, M., Riposo, J., Wallace, W., and Yener, B. 2003. Statistical modeling of social groups on communication networks. In Proceedings of the 1st Conference of the North American Association for Computational Social and Organizational Science.
[19]
Grimm, V. and Railsback, S. F. 2005. Individual-Based Modeling and Ecology. Princeton series in theoretical and computational biology. Princeton University Press, Princeton, NJ.
[20]
Hoff, P., Raftery, A., and Handcock, M. 2002. Latent space approaches to social network analysis. J. Amer. Statis. Assoc., 1090--1098.
[21]
Kadushin, C. 2004. Too much social capital? Soc. Netw. 26, 75--90.
[22]
Kohler, T. A. and Gumerman, G. J. 2000. Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes. Oxford University Press, New York, NY.
[23]
Kohler, T. A., Johnson, D. C., Varien, M., Ortman, S., Reynolds, R., Kobti, Z., Cowan, J., Kolm, K., Smith, S., and Yap, L. 2007. Settlment ecodynamics in the prehispanic central mesa verde region. In The Model-Based Archaeology of Socionatural Systems, T. A. Kohler and S. E. van der Leeuw, Eds. SAR Press, Santa Fe, NM.
[24]
Kraut, R., Olson, J., Banaji, M., Bruckman, A., Cohen, J., and Couper, M. 2004. Psychological reserach online: Report of board of scientific affairs' advisory group on the conduct of research on the internet. Amer. Psych. 59, 2, 105--117.
[25]
Kuznar, L. A. and Sedlmeyer, R. 2005. Collective violence in darfur: An agent-based model of pastoral nomad/sedentary peasant interaction. Math. Anthr. Cult. Theory: Int. J. 1, 4, 22.
[26]
Lustick, I. S. and Miodownik, D. 2002. The institutionalization of identity: Micro adaptation, macro effects, and collective consequences. Studies Compar. Int. Devel. 37, 2, 24--53.
[27]
Marsden, P. V. 1990. Network data and measurement. Ann. Rev. Sociol. 16, 435--463.
[28]
Miles, M. and Huberman, A. 1994. Qualitative Data Analysis: An Expanded Sourcebook. Sage Publications.
[29]
Minar, N., Burkhardt, R., Langston, C., and Askanazi, M. 1996. The Swarm simulation system: A toolkit for building multi-agent simulations. Tech. rep., Sante Fe Institute.
[30]
Monge, P. R. and Contractor, N. S. 2003. Theories of Communication Networks. Oxford University Press, Oxford, UK.
[31]
North, M. J., Collier, N. T., and Vos, J. R. 2006. Experiences creating three implementations of the Repast Agent Modeling Toolkit. ACM Trans. Model. Comput. Simul. 10, 2, 1--25.
[32]
Ortner, S. B. 2003. New Jersey Dreaming: Capital, Culture, and the Class of '58. Duke, University Press.
[33]
Parker, M. T. 2001. What is Ascape and why you should care? The J. Artif. Soc. Social Simul. 4, 1, http://www.soc.surrey.ac.uk/JASSS/4/1/5.html.
[34]
Portes, A. 1998. Social capital: Its origins and applications in modern sociology. Ann. Rev. Sociol. 24, 1--24.
[35]
Putnam, R. D. 2000. Bowling Alone: The Collapse and Revival of American Community. Simon and Schuster, New York, NY.
[36]
Sallach, D. L. 2003. Social theory and agent architectures: prospective issues in rapid-discovery social science. Soc. Sci. Comput. Rev. 21, 2, 175--195.
[37]
Sallach, D. L. and Mellarkod, V. S. 2005. Typifying situations: Contextualizing and cohering action. In Proceedings of the North American Association for Computational Social and Organizational Science (NAACSOS'05). Notre Dame, IN.
[38]
Sanil, A., Banks, D., and Carley, K. 1996. Models for evolving fixed node networks: Model fitting and model testing. J. Math. Sociol. 21, 1-2, 173--196.
[39]
Sarkar, P. and Moore, A. 2005. Dynamic social network analysis using latent space models. ACM SIGKDD Explorations Newsletter, 31--40.
[40]
Sierhuis, M., Clancey, W. J., Seah, C., Trimble, J. P., and Sims, M. H. 2003. Modeling and simulation for mission operations work system design. J. Manag. Inform. Sys. 19, 4, 85--128.
[41]
Snijders, T. 2001. The statistical evaluation of social network dynamics. In Sociological Methodology Dynamics, M. Sobel and M. Becker, Eds. Basil Blackwell, London, UK, 361--395.
[42]
Somekh, B. and Lewin, C., Eds. 2005. Research Methods in the Social Sciences. Sage Publications Ltd.
[43]
Van der Veen, A. M., Lustick, I. S., and Miodownik, D. 2001. Studying performance and learning with ABIR. Social Sci. Comput. Rev. 19, 3, 263--280.
[44]
Wasserman, S. and Faust, K. 1994. Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge, UK.
[45]
Zuboff, S. 1988. In the Age of the Smart Machine. Heinemann.
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- ViSAGE: A Virtual Laboratory for Simulation and Analysis of Social Group Evolution
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Publication History
Published: 13 August 2008
Accepted: 01 June 2008
Revised: 01 January 2008
Received: 01 February 2007
Published in TAAS Volume 3, Issue 3
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View all- CHEN HGOLDBERG MMAGDON-ISMAIL MWALLACE W(2008)REVERSE ENGINEERING A SOCIAL AGENT-BASED HIDDEN MARKOV MODEL — ViSAGEInternational Journal of Neural Systems10.1142/S012906570800175018:06(491-526)Online publication date: Dec-2008
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