Dr. Huskey is a Ph.D. graduate from the Department of Communication and a former member of the Media Neuroscience Lab. is an assistant professor in the Department of Communication and the Cognitive Science Program at the University of California Davis. The Media Neuroscience Lab is hosting his talk, "Formalizing Media Selection With Computational Models" February 22nd at 9 AM in SSMS 1009.
How and why people select media is one of the oldest questions in Communication Science. In entertainment contexts, many theories argue that people select media that will help them achieve or maintain a positive affective state. However these theories are typically instantiated in what are known as “verbal models” in which constructs central to a theory, and their relationships, are verbally described. Verbal theories are powerful, but often ambiguous, which makes it hard to know when a verbal theory has been adequately supported or falsified. Computational models reduce this ambiguity by translating verbal descriptions into precise mathematical relationships. In this talk, I will demonstrate how a verbal model of media selection can be translated into a computational model and the theoretical contributions that result. I will begin with a meta-theoretic argument for the importance of computational modeling. Subsequently, I will introduce the drift diffusion model (DDM), and explain how the DDM can be applied to formalize a prominent theory of media selection. Finally, I will present three pre-registered experiments using the DDM and showcase results that falsify core theoretical predictions, expose boundary conditions, and identify new media selection mechanisms.