  In this paper, we study a model for opinion dynamics where the influence
weights of agents evolve in time via an equation which is coupled with the
opinions' evolution. We explore the natural question of the large population
limit with two approaches: the now classical mean-field limit and the more
recent graph limit. After establishing the existence and uniqueness of
solutions to the models that we will consider, we provide a rigorous
mathematical justification for taking the graph limit in a general context.
Then, establishing the key notion of indistinguishability, which is a necessary
framework to consider the mean-field limit, we prove the subordination of the
mean-field limit to the graph one in that context. This actually provides an
alternative (but weaker) proof for the mean-field limit. We conclude by showing
some numerical simulations to illustrate our results.
