Psychological Meme Science
dc.contributor.advisor | Cupchik, Gerald C | |
dc.contributor.author | Miller, Ian Dennis | |
dc.contributor.department | Psychology | |
dc.date | 2019-11 | |
dc.date.accepted | 2019-11 | |
dc.date.accessioned | 2019-11-14T18:00:39Z | |
dc.date.available | 2019-11-14T18:00:39Z | |
dc.date.convocation | 2019-11 | |
dc.date.issued | 2019-11 | |
dc.description.abstract | Memes are ideas, often represented using media, with the special characteristics of being repeatable and adaptable. Memes impact our lives in material ways, influencing political systems and propagating the stories our shared culture is built from. When propagated via online social networks, the massive scale at which memes operate is without precedent. However, the meme does not act on its own; it is only by human activity that memes are created and proliferated. This dissertation will tackle a series of research questions surrounding the scientific study of humans and memes from a psychological perspective. This work begins with the observation that science is a social enterprise and scientific ideas spread as memes. The first chapter of this dissertation applies social network methods to the global scientific collaboration network in order to build a map of beliefs about systems of humans and memes. The next chapter examines a hierarchical democratic phenomenon - the online campaign preceding an election - in order to determine the appropriate analytical scope for investigating complex systems of political memes. The final chapter presents a method for translating regression models from the psychological literature into computational social simulations using agent-based models. A computational social simulation of urban legends is then built, replicating a study from the literature and then extending it to examine the effect of social network topology upon the propagation of urban legends. Humans and memes, together, constitute a complex system that offers new methodological tools to study the human condition. | |
dc.description.degree | Ph.D. | |
dc.identifier.uri | http://hdl.handle.net/1807/97595 | |
dc.subject | agent-based modeling | |
dc.subject | computational social science | |
dc.subject | election campaigns | |
dc.subject | memes | |
dc.subject | social networks | |
dc.subject | urban legends | |
dc.subject.classification | 0451 | |
dc.title | Psychological Meme Science | |
dc.type | Thesis |
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