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dc.contributor.authorKuhlman, Christopher J.en_US
dc.date.accessioned2015-01-09T07:00:12Z
dc.date.available2015-01-09T07:00:12Z
dc.date.issued2013-07-17en_US
dc.identifier.othervt_gsexam:615en_US
dc.identifier.urihttp://hdl.handle.net/10919/51175
dc.description.abstractDynamics of social processes in populations, such as the spread of emotions, influence, opinions, and mass movements (often referred to individually and collectively as contagions), are increasingly studied because of their economic, social, and political impacts. Moreover, multiple contagions may interact and hence studying their simultaneous evolution is important. Within the context of social media, large datasets involving many tens of millions of people are leading to new insights into human behavior, and these datasets continue to grow in size. Through social media, contagions can readily cross national boundaries, as evidenced by the 2011 Arab Spring. These and other observations guide our work. Our goal is to study contagion processes at scale with an approach that permits intricate descriptions of interactions among members of a population. Our contributions are a modeling environment to perform these computations and a set of approaches to predict contagion spread size and to block the spread of contagions. Since we represent populations as networks, we also provide insights into network structure effects, and present and analyze a new model of contagion dynamics that represents a person\'s behavior in repeatedly joining and withdrawing from collective action. We study variants of problems for different classes of social contagions, including those known as simple and complex contagions.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectSocial behavioren_US
dc.subjectContagionsen_US
dc.subjectNetworksen_US
dc.subjectControl of contagion processesen_US
dc.subjectGraph dynamical systemsen_US
dc.subjectModeling and simulationen_US
dc.subjectRapid den_US
dc.titleHigh Performance Computational Social Science Modeling of Networked Populationsen_US
dc.typeDissertationen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Science and Applicationsen_US
dc.contributor.committeechairMarathe, Madhav Vishnuen_US
dc.contributor.committeememberTilevich, Elien_US
dc.contributor.committeememberRavi, Sekharipuramen_US
dc.contributor.committeememberMortveit, Henning S.en_US
dc.contributor.committeememberVullikanti, Anil Kumar S.en_US


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