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dc.contributor.authorKrishnan, Siddharthen_US
dc.date.accessioned2018-05-19T08:00:17Z
dc.date.available2018-05-19T08:00:17Z
dc.date.issued2018-05-18
dc.identifier.othervt_gsexam:16470en_US
dc.identifier.urihttp://hdl.handle.net/10919/83362
dc.description.abstractCascades are a popular construct to observe and study information propagation (or diffusion) in social media such as Twitter and are defined using notions of influence, activity, or discourse commonality (e.g., hashtags). While these notions of cascades lead to different perspectives, primarily cascades are modeled as trees. We argue in this thesis an alternative viewpoint of cascades as forests (of trees) which yields a richer vocabulary of features to understand information propagation. We propose to develop a framework to extract forests and analyze their growth by studying their evolution at the tree-level and at the node-level. Furthermore, we outline four different problems that use the forest framework. First, we show that such forests of information cascades can be used to design counter-contagion algorithms to disrupt the spread of negative campaigns or rumors. Secondly, we demonstrate how such forests of information cascades can give us a rich set of features (structural and temporal), which can be used to forecast information flow. Thirdly, we argue that cascades modeled as forests can help us glean social network sensors to detect future contagious outbreaks that occur in the social network. To conclude, we show preliminary results of an approach - a generative model, that can describe information cascades modeled as forests and can generate synthetic cascades with empirical properties mirroring cascades extracted from Twitter.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.subjectInformation cascadesen_US
dc.subjectForecastingen_US
dc.titleSeeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascadesen_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.committeechairHeath, Lenwood S.en_US
dc.contributor.committeememberRas, Zbigniew W.en_US
dc.contributor.committeememberMitra, Tanushreeen_US
dc.contributor.committeememberRibbens, Calvin J.en_US
dc.contributor.committeememberMarathe, Madhav Vishnuen_US


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