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Opinion dynamics simulation from real world data 1.0.0
This is an opinion dynamics simulation using Jupiter notebook with python. In the code agents interact in random pairs (as in a fully connected graph) and agent 1 changes her opinion depending on the opinion of agent 2.
The code uses three main effects:
a) Social influence (i.e. agent 1 moves in the direction of agent 2)
b) Flipping (i.e. agent 1 has a certain probability of changing her agreement level, while preserving her certainty)
c) Certainty-induced noise (i.e. the opinion of the agent has some random fluctuations whose amplitude depends on the initial
The values of these rules are determined from experiments with participants.
Release Notes
First version