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A framework for the calibration of social simulation models

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Publication date 2013
Project Production and consumption of information in large-scale social media
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Original article (peer-reviewed)

Journal Advances in Complex Systems
Volume (Issue) 16(4-5)
Page(s) n05
Title of proceedings Advances in Complex Systems
DOI 10.1142/S0219525913500306

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. © 2013 World Scientific Publishing Company.
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