This paper introduced a new approach to social science modeling in which the participants themselves are motivated to uncover the correlates of some human behavior outcome, such as homeowner electricity usage or body mass index. In both cases participants successfully uncovered at least one statistically significant predictor of the outcome variable. For the body mass index outcome, the participants successfully formulated many of the correlates known to predict BMI, and provided sufficiently honest values for those correlates to become predictive during the experiment. While, our instantiations focus on energy and BMI, the proposed method is general, and might, as the method improves, be useful to answer many difficult questions regarding why some outcomes are different than others. This paper introduces, for the first time, a method by which non domain experts can be motivated to formulate independent variables as well as populate enough of these variables for successful modeling. In short, this is accomplished as follows. Users arrive at a website in which a behavioral outcome is to be modeled. Users provide their own outcome (such as their own BMI) and then answer questions that may be predictive of that outcome (such as ‘how often per week do you exercise’). Periodically, models are constructed against the growing data set that predicts each user’s behavioral outcome. The first instantiation of this concept, The developed a web-based social network to model residential electric energy consumption. Because of policy efforts to increase energy efficiency, many are working to provide consumers with better information about their energy consumption. Research on consumer perception of energy efficiency indicates that electricity customers often misjudge the relative importance of various activities and devices to reducing energy consumption. To provide customers with better information, numerous expert driven web-based tools have been deployed. In some cases these tools use social pressure as a means of improving energy efficiency.
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