readme.md~

# Activation Regimes in Opinion Dynamics

Code for my paper [Alizadeh and Cioffi (2015)](http://jasss.soc.surrey.ac.uk/18/3/8.html). 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.