Effect of the media on the opinion dynamics in online social networks

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I am studying a paper called "Effect of the media on the opinion dynamics in online social networks" and I cannot understand a passage.

Let's first define a matrix A (n x n) which elements are $a_{ij}=\frac{1-v_i}{(1-v_i)d_i+v_i}$ where $v_i$ can assume values from 0 to 1 (continuous values) and $d_i$ can assume values from 1 to n-1 (discrete values).

I don't understand this passage:

"Matrix A meets the conditions (1) $a_{ij} \ge 0 \forall i,j$ and (2) $\sum_j{a_{ij}} \le 1 \forall i$, so is sub-stochastic matrix which can’t be reduced. Define $\rho (A)=max_i|\lambda_i(A)|$ as the spectral radius of A. According to the Perron-Frobenius theorem, the largest eigenvalue of A should be positive, where $ 0<\lambda_1<1$ and $\rho(A)=\lambda_1$. Hence, $lim_{T\rightarrow \infty}A^T=0$."

My problems are:

  • Why does $ 0<\lambda_1<1$ holds and how can I prove it? Is it a consequence of the fact that A is sub-stochastic? or is it a consequence of the Perron-Freobenius theorem?

  • Why does the limit hold and how can I prove it?

Someone can help? Thank you in advance! :)

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Yes, $0 < \lambda_1 < 1$ is stated to be a consequence of the Perron-Frobenius theorem (cf. , e.g., point 11 in the list under "Statement" in the linked Wikipedia page).

The limit of $A^T$ for $T \rightarrow \infty$ is dominated by a contribution from the largest eigenvalue (the eigenvalue with the largest absolute value), which behaves as $\lambda_1^T$. Which goes to zero because $0 < \lambda_1 < 1$. This is also mentioned in the Wikipedia article:

The exponential growth rate of the matrix powers Ak as k → ∞ is controlled by the eigenvalue of A with the largest absolute value (modulus).