1. A method, comprising: identifying, by an electronic apparatus, one user's connections with other users in an electronic social network; creating, by the electronic apparatus, a data structure in a memory that represents the one user, the other users, and the one user's connections with the other users; analyzing, by the electronic apparatus, a plurality of data sources for electronic communications between the one user and the other users including assigning a relative importance value to each data source of the plurality of data sources and assigning a weight to each of the connections between the one user and the other users, wherein the weight is an encoded value computed based on a link structure of the connections, the link structure including metadata indicating a category and a status of a respective connection(s), the weight enabling an emulation and behavioral prediction of the electronic social network in response to a stimulus applied to the electronic social network; calculating, by the electronic apparatus, for each of the other users a probability that the one user will communicate with that other user based on the analyzed plurality of data sources; ranking, by the electronic apparatus, the one user's connections with the other users based on the calculated probabilities; removing from the data structure one or more data structure elements of the one user's connections based on the ranked one user's connections to create a signature graph; and forming a diagnostic model of the electronic social network, the diagnostic model including the signature graph to accelerate a processing speed of the diagnostic model on a social network analysis system.