Measuring the social preferences of economic agents using experiments has become common place. This process, while incentive compatible, is costly and time consuming, making it infeasible in many settings. We combine standard altruism and warm glow choice experiments with a battery of candidate survey questions to construct behaviorally-validated questionnaires. We use machine learning to create parsimonious 3-question modules that reliably replicate existing results on general altruism and provide an alternative method for collecting warm glow preferences.