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Manuel Jiménez-Martín

Publications and source records attributed to Manuel Jiménez-Martín.

2 recordsLinked to original sources

A null model for Dunbar's circles

An individual's social group may be represented by their ego-network, formed by the links between the individual and their acquaintances. Ego-networks present an internal structure of increasingly large nested layers (or circles) of decreasing relationship intensity, whose size exhibits a precise scaling ratio. Starting from the notion of limited social bandwidth, and assuming fixed costs for the links in each layer, we propose a null model built on a grand-canonical ensemble that generates the observed hierarchical social structure. The observed internal structure of ego-networks becomes a natural outcome to expect when we assume the existence of layers demanding different amounts of resources. In the thermodynamic limit, reached when the number of ego-network copies is large, the specific layer degrees follow a Poisson distribution. We also find that, under certain conditions, equispaced layer costs are necessary to obtain a constant group size scaling. Our model presents interesting analogies to a Bose-Einstein gas, that we briefly discuss. Finally, we fit and compare the model with an empirical social network.

physics.soc-ph↗

Link aggregation process for modelling weighted mutualistic networks

Mutualism is a biological interaction mutually beneficial for both species involved, such as the interaction between plants and their pollinators. Real mutualistic communities can be understood as weighted bipartite networks and they present a nested structure and truncated power law degree and strength distributions. We present a novel link aggregation model that works on a strength-preferential attachment rule based on the Individual Neutrality hypothesis. The model generates mutualistic networks with emergent nestedness and truncated distributions. We provide some analytical results and compare the simulated and empirical network topology. Upon further improving the shape of the distributions, we have also studied the role of forbidden interactions on the model and found that the inclusion of forbidden links does not prevent for the appearance of super-generalist species. A Python script with the model algorithms is available.

q-bio.PE↗