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dc.contributor.authorHuynh, Dangde
dc.contributor.authorRodrigues, Nilsde
dc.contributor.authorRumberger, Reinholdde
dc.date.accessioned2013-12-03de
dc.date.accessioned2016-03-31T08:00:56Z-
dc.date.available2013-12-03de
dc.date.available2016-03-31T08:00:56Z-
dc.date.issued2013de
dc.identifier.other398695431de
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-88336de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/3212-
dc.identifier.urihttp://dx.doi.org/10.18419/opus-3195-
dc.description.abstractPeople use social networks, with increasing frequency, to communicate and publish status information. Twitter and Facebook are prominent examples. This status information contains useful, disaster related data together with an overwhelming amount of noise. For this reason, there are dedicated tools that filter this information to aid in disaster discovery, management and relief. Their development requires a lot of time and effort, which results in high costs. Generic visual analytics tools are relatively well known, supported and continuously developed by large companies. They may be a valid alternative to specifically developed tools that require specific, non-transferable training. The primary aim of this study is to evaluate generic visual analytics tools with respect to their ability to handle disaster management scenarios. This includes, specifically, their ability to visualise and analyse the geospatial meta information provided by social media.en
dc.language.isoende
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddc004de
dc.titleSocial media analysis for disaster managementen
dc.typeStudyThesisde
ubs.fakultaetFakultät Informatik, Elektrotechnik und Informationstechnikde
ubs.institutInstitut für Visualisierung und Interaktive Systemede
ubs.opusid8833de
ubs.publikation.typStudienarbeitde
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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