Spatio-Temporal Storytelling on Twitter

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dc.contributor.authorDos Santos Jr, Raimundo F.en
dc.contributor.authorShah, Sumiten
dc.contributor.authorChen, Fengen
dc.contributor.authorBoedihardjo, Arnold P.en
dc.contributor.authorButler, Patricken
dc.contributor.authorLu, Chang-Tienen
dc.contributor.authorRamakrishnan, Narenen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-12-16T20:32:00Zen
dc.date.available2013-12-16T20:32:00Zen
dc.date.issued2013-12-16en
dc.description.abstractSocial media, e.g.,Twitter, have provided us an unprecedented opportunity to observe events un-folding in real-time. The rapid pace at which situations play out on social media necessitates new tools for capturing and summarizing the spatio-temporal progression of events. This technical report describes methods for generating dynamic real-world storylines from Twitter Sources and shares the results of related experiments.en
dc.identifier.trnumberTR-13-06en
dc.identifier.urihttp://hdl.handle.net/10919/24701en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectAlgorithmsen
dc.subjectData structuresen
dc.subjectInformation retrievalen
dc.subjectSpatio-temporal analysisen
dc.subjectSemantic networksen
dc.subjectGraph networksen
dc.titleSpatio-Temporal Storytelling on Twitteren
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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