Computational Approaches to Behavior cluster description
Large datasets are everywhere, and track everything from social networks to mental health. These records reflect the systematicity and the underlying connectedness of public behaviors. In order to make effective use of these datasets, corporations, governments, and organizations need individuals who can distill reliable patterns from these records, and who can identify causal links by modeling the relationships among these data. Classes associated with this cluster focus on how behavior can be quantified mathematically, and how a diverse set of tools can be used to uncover the underlying patterns. These tools can be used to track factors such as the efficacy of mental health treatments, the spread of suicide epidemics, and the areas of the brain associated with attention.