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Activation Regimes in Opinion Dynamics

Code for my paper Alizadeh and Cioffi (2015). I apply four different asynchronous updating schemes including random, uniform, and two state-driven Poisson updating schemes on an agent-based opinion dynamics model. We compare the effect of these activation regimes by measuring the appropriate opinion clustering statistics and also the number of emergent extremists.

Huet2008.py contains the original CBC model code (Huet et al 2008).

Random_AR.py contains the code for Random activation regime applying on the CBC model.

Uniform_AR.py contains the code for Uniform activation regime applying on the CBC model.

Poisson1_AR.py contains the code for Poisson activation regime applying on the CBC model when more extreme agents have have more interaction probability.

Poisson2_AR.py contains the code for Poisson activation regime applying on the CBC model when moderate agents have higher chance of interaction.

No_Clusters.py computes the number of opinion clusters.

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