An improved approach for ecological modeling of social phenomena in Blau space

Advances in computation have opened new vistas for modeling of sociodemographic niches and related constructs, enabling us to rectify limitations that unavoidably plagued earlier generations of researchers. This is especially true for Blau space, a sociodemographic niche model used to explore competition between social entities over resources, such as memberships. While this approach has been successful in using probabilistic representations of social networks and resource niches, its modeling framework has remained essentially unchanged for over 40 years, and lacks the ability to make predictions about the future states of sociodemographic space. We present a novel Hybrid Blau space (HBS) model, which utilizes a cellular framework and probabilistic urn models to simulate competition over resources while suffering from fewer limitations. We apply this new model to the General Social Survey, running two sets of models from a series of variables (age, education, income, and sex) and utilize an adjustable range of sociodemographic information for local simulation of organizational competition. We also demonstrate the model's predictive ability, as well as introduce new methods of validation and fit.