Abstract
Finding suitable analysis techniques for networks generated from social processes is a difficult task when the population changes over time. Traditional social network analysis measures may not work in such circumstances. It is argued that agent-based social networks should not be constrained by a priori assumptions about the evolved network and/or the analysis techniques. In most agent-based social simulation models, the number of agents remains fixed throughout the simulation; this paper considers the case when this does not hold. Thus the aim of this paper is to demonstrate how the network signatures change when the agents’ population depends upon endogenous social processes. We argue for a much wider attention from the social simulation community in addressing this open research problem.
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Alam, S.J., Edmonds, B., Meyer, R. (2009). Identifying Structural Changes in Networks Generated from Agent-Based Social Simulation Models. In: Ghose, A., Governatori, G., Sadananda, R. (eds) Agent Computing and Multi-Agent Systems. PRIMA 2007. Lecture Notes in Computer Science(), vol 5044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01639-4_26
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DOI: https://doi.org/10.1007/978-3-642-01639-4_26
Publisher Name: Springer, Berlin, Heidelberg
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