COMPUTATIONAL SOCIAL SCIENCE

Department of Computational Social Science Seminar - Casstevens Oral Dissertation Defense

Wednesday, December 19 - 10:00 a.m.
Center for Social Complexity Suite
Research Hall, Third Floor

Innovation from a Computational Social Science Perspective: Analyses and Models

Randy Casstevens, PhD Candidate
Department of Computational Social Science
George Mason University

Abstract: Abstract: Innovation is the most critical economic process for preserving and improving our standard of living. While innovation has been studied by many disciplines, the focus has been on qualitative measures that are specific to a single technological domain. Here a quantitative approach of innovation study is used to discover underlying regularities that may generalize across multiple technologies. I am using a revolutionary approach, heretofore unexploited, to better understand the innovation process by combining agent-based models with empirical software development data (i.e., MATLAB programming contests) and word frequency data (i.e., Google Books data). Innovation can be viewed as the recombination and mutation of existing building blocks. Therefore, this dissertation focuses on how building blocks are used to generate innovations. The building blocks are pieces of code (i.e., functions) for the software development data and words for the word frequency data. These data sets lie at extremes; one demonstrates an innovation process that occurs over the course of a week and the other over the course of a century. This allows the examination of innovation processes that range from well-defined problems to one that is completely open-ended. Computational models reinforce the findings from the data analyses and further expand them to areas of inquiry beyond what the empirical data can support.