A human behavior modeling Paradigm in cyber infrastructure

There are many problems in which one seeks to develop predictive models to map between a set of predictor variables and an outcome. Statistical tools such as multiple regression or neural networks provide mature methods for computing model parameters when the set of predictive covariates and the model structure are pre-specified. Furthermore, recent research is providing new tools for inferring the structural form of non-linear predictive models, given good input and output data . The task of choosing which potentially predictive variables to study is largely a qualitative task that requires substantial domain expertise. For example, a survey designer must have domain expertise to choose questions that will identify predictive covariates. An engineer must develop substantial familiarity with a design in order to determine which variables can be systematically adjusted in order to optimize performance. The need for the involvement of domain experts can become a bottleneck to new insights. If the wisdom of crowds could be harnessed to produce insight into difficult problems, one might see exponential rises in the discovery of the causal factors of behavioral out comes, mirroring the exponential growth on other online collaborative communities. Thus, the goal of this research was to test an alternative approach to modeling in which the wisdom of crowds is harnessed to both propose potentially predictive variables to study by asking questions, and respond to those questions, in order to develop a predictive model.