| \(t\) |
Time. |
| \(N\) |
Number of nodes in the network. |
| \(\mathbf{A}\) |
The \(N \times N\) adjacency matrix of the social network. A discrete function of time. Entries are the weights of the edges connecting the \(i\)-th and \(j\)-th nodes. |
| \(\mathbf{T}\) |
An \(N \times N\) interaction matrix. Entries are \(1\) or \(0\) denoting whether nodes \(i\) and \(j\) interact at time \(t\). |
| \(\mathbf{M}\) |
An \(N \times N\) matrix of uniform random numbers between \(0\) and \(1\). Used to determine which nodes interact at time \(t\). |
| \(\mathbf{\theta}\) |
A length \(N\) column vector of node attitudes. |
| \(\mathbf{\Theta}\) |
An \(N \times N\) matrix of differences between attitudes \(\mathbf{\theta}\) of the nodes in the network. |
| \(\mathbf{\alpha}\) |
Scaling parameter governing the dependence of attitude reinforcement on the adjacency matrix. This is a complexity parameter. |
| \(\mathbf{\beta}\) |
Scaling parameter governing the rate of attitude change. Smaller values slow change. |