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A Framework For The Calibration Of Social Simulation Models

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  • GIOVANNI LUCA CIAMPAGLIA

    (Center for Complex Networks and Systems Research, School of Informatics and Computing, Indiana University, 919 E 10th St., Bloomington, IN 47408, USA)

Abstract

Simulation with agent-based models is increasingly used in the study of complex socio-technical systems and in social simulation in general. This paradigm offers a number of attractive features, namely the possibility of modeling emergent phenomena within large populations. As a consequence, often the quantity in need of calibration may be a distribution over the population whose relation with the parameters of the model is analytically intractable. Nevertheless, we can simulate. In this paper we present a simulation-based framework for the calibration of agent-based models with distributional output based on indirect inference. We illustrate our method step by step on a model of norm emergence in an online community of peer production, using data from three large Wikipedia communities. Model fit and diagnostics are discussed.

Suggested Citation

  • Giovanni Luca Ciampaglia, 2013. "A Framework For The Calibration Of Social Simulation Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-29.
    • Handle: RePEc:wsi:acsxxx:v:16:y:2013:i:04n05:n:s0219525913500306
    DOI: 10.1142/S0219525913500306
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    References listed on IDEAS

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    1. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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    Cited by:

    1. Giovanni Luca Ciampaglia, 2018. "Fighting fake news: a role for computational social science in the fight against digital misinformation," Journal of Computational Social Science, Springer, vol. 1(1), pages 147-153, January.

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