Social Networks and Spatial Distribution

Part of the Understanding Complex Systems book series (UCS)

Why Read This Chapter?

To learn about interaction topologies for agents, from social networks to structures representing geographical space, and the main questions and options an agent-based modeller has to face when developing and initialising a model.


In most agent-based social simulation models, the issue of the organisation of the agents’ population matters. The topology, in which agents interact, – be it spatially structured or a social network – can have important impacts on the obtained results in social simulation. Unfortunately, the necessary data about the target system is often lacking, therefore you have to use models in order to reproduce realistic spatial distributions of the population and/or realistic social networks among the agents. In this chapter we identify the main issues concerning this point and describe several models of social networks or of spatial distribution that can be integrated in agent-based simulation to go a step forward from the use of a purely random model. In each case we identify several output measures that allow quantifying their impacts.


Random Graph Degree Distribution Cluster Coefficient Regular Graph Preferential Attachment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.IRITUniversité Toulouse 1 CapitoleToulouseFrance
  2. 2.LABSSUniversity of SienaSienaItaly

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