Scalable Analysis for Large Social Networks: The Data-Aware Mean-Field Approach
Studies on social networks have proved that endogenous and exogenous factors influence dynamics. Two streams of modeling exist on explaining the dynamics of social networks: models predicting links through network properties, and models considering the effects of social attributes. In this interdisciplinary study, the authors paper to overcome a number of computational limitations within these current models. They employ a mean-field model which allows for the construction of a population-specific model informed from empirical research for predicting links from both network and social properties in large social networks. The model is tested on a population of conference coauthorship behavior, considering a number of parameters from available Web data.