Modeling scientific-citation patterns and other triangle-rich acyclic networks

We propose a model of the evolution of the networks of scientific citations. The model takes an out-degree distribution (distribution of number of citations) and two parameters as input. The parameters capture the two main ingredients of the model: the aging of the relevance of papers and the formation of triangles when new papers cite old. We compare our model to three network structural quantities of an empirical citation network. We find that unique point in parameter space optimizing the match between the real and model data for all quantities. The optimal parameter values suggest that the impact of scientific papers, at least in the empirical data set we model, is proportional to the inverse of the number of papers since they were published.

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