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Innovation from a Computational Social Science Perspective: Analyses and Models

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dc.contributor.advisor Axtell, Robert L.
dc.contributor.author Casstevens, Randy M.
dc.creator Casstevens, Randy M. en_US
dc.date.accessioned 2013-08-09T15:38:52Z
dc.date.available 2013-08-09T15:38:52Z
dc.date.issued 2013 en_US
dc.identifier.uri https://hdl.handle.net/1920/8251
dc.description.abstract Innovation processes are critical 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. I adopt a quantitative approach to investigate underlying regularities that generalize across multiple domains. I use a novel approach to better understand the innovation process by combining computational models with empirical data on software development, on one hand, and the evolution of the English lexicon on the other. Innovation can be viewed as the recombination and mutation of existing building blocks. I focus on how building blocks are used to generate innovations. The building blocks are pieces of code (e.g., functions or objects) for the software development data and words for the written language. These data lie at extremes of time scales: innovation occurring over the course of a few days or a week in the case of software while language evolution occurs over decades or centuries. This allows the examination of innovation processes that range from highly-constrained to completely open-ended. Computational methods reinforce the findings from the data analyses and permit exploration of the general features of innovation processes through the construction of abstract models.
dc.format.extent 236 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2013 Randy M. Casstevens en_US
dc.subject Computer science en_US
dc.subject Sociology en_US
dc.subject Linguistics en_US
dc.subject Agent-Based Modeling en_US
dc.subject Evolutionary Computation en_US
dc.subject Google Books Corpus en_US
dc.subject Innovation en_US
dc.subject MATLAB Programming Contest en_US
dc.subject Technological Evolution en_US
dc.title Innovation from a Computational Social Science Perspective: Analyses and Models en_US
dc.type Dissertation en
thesis.degree.level Doctoral en
thesis.degree.discipline Computational Social Science en
thesis.degree.grantor George Mason University en


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  • Krasnow Institute for Advanced Study
    Seeking to understand the human mind: how it came to be, how it relates to the electrochemical activities of networks of nerve cells in the brain, how it can be modeled on computers, and how it is a vital component of what we are.

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