An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition

Table 3

The initial parameters of the model.

Parameters	Value
Node states:	U [1, 10]
Node states dimension: r	4
Model iterations: it	2000
Update parameter of state: μ	0.5

To highlight the difference between node states, the value of the node state is set to a uniform continuous distribution in the range of [1, 10]. At the same time, the dimension of the node state is limited to 4 to effectively distinguish states between nodes. The time complexity of the model implementation is affected by the size of the link M. Therefore, the number of iterations is set to 2000 to ensure the effect of simulation. Also, update parameters of state μ are set to 0.5 along with the existing model’s setting.