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dc.contributor.authorKahlert, Roland
dc.contributor.authorLiebeck, Matthias
dc.contributor.authorCornelius, Joseph
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-21T11:24:42Z
dc.date.available2017-06-21T11:24:42Z
dc.date.issued2017
dc.identifier.isbn978-3-88579-660-2
dc.identifier.issn1617-5468
dc.description.abstractMany events, for instance in sports, political events, and entertainment, happen all over the globe all the time. It is difficult and time consuming to notice all these events, even with the help of different news sites. We use tweets from Twitter to automatically extract information in order to understand hashtags of real-world events. In our paper, we focus on the topic identification of a hashtag, analyze the expressed positive, neutral, and negative sentiments of users, and further investigate the expressed emotions. We crawled English tweets from 24 hashtags and report initial investigation results.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-266
dc.subjectText Mining
dc.subjectTopic Recognition
dc.subjectSentiment Analysis
dc.subjectEmotion Detection
dc.subjectTwitter
dc.titleUnderstanding Trending Topics in Twitteren
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages375-384
mci.conference.sessiontitleStudierendenprogramm
mci.conference.locationStuttgart
mci.conference.date6.-10. März 2017


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