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dc.rights.licenseUsers may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.
dc.contributorMagdon-Ismail, Malik
dc.contributorGoldberg, Mark
dc.contributorSzymanśki, Bolesław
dc.contributorWallace, William A., 1935-
dc.contributor.authorThompson, James
dc.date.accessioned2021-11-03T08:24:55Z
dc.date.available2021-11-03T08:24:55Z
dc.date.created2015-06-09T13:40:03Z
dc.date.issued2015-05
dc.identifier.urihttps://hdl.handle.net/20.500.13015/1439
dc.descriptionMay 2015
dc.descriptionSchool of Science
dc.description.abstractThe purpose of this research is to study the structure of social networks with an added temporal element. Specifically, we examine dynamic community behavior within social networks. We base our experiments on a simple theoretical foundation which allows us to efficiently identify dynamic community evolutions. Based on this framework, we empirically study evolutions in large social networks and structural features of evolutions across all networks. Results show that structural properties remain similar across multiple social networks and it is possible to correlate the lifespan of a community to specific features of its early evolution.
dc.description.abstractWe also develop a framework for generating social networks with structures similar to those found in real world systems. Using this framework, we examine the behavior of evolution detection algorithms in full networks and more isolated situations. Finally we examine the robustness of our developed community evolution tracking framework in noisy systems.
dc.language.isoENG
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectComputer science
dc.titleCommunity evolution in temporal networks
dc.typeElectronic thesis
dc.typeThesis
dc.digitool.pid175885
dc.digitool.pid175886
dc.digitool.pid175887
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
dc.description.degreePhD
dc.relation.departmentDept. of Computer Science


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