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In this paper, we study a model for opinion dynamics where the influenceweights of agents evolve in time via an equation which is coupled with theopinions' evolution. We explore the natural question of the large populationlimit with two approaches: the now classical mean-field limit and the morerecent graph limit. After establishing the existence and uniqueness ofsolutions to the models that we will consider, we provide a rigorousmathematical justification for taking the graph limit in a general context.Then, establishing the key notion of indistinguishability, which is a necessaryframework to consider the mean-field limit, we prove the subordination of themean-field limit to the graph one in that context. This actually provides analternative (but weaker) proof for the mean-field limit. We conclude by showingsome numerical simulations to illustrate our results.

Mean-field and graph limits for collective dynamics models with time-varying weights