Understanding Trending Topics in Twitter
dc.contributor.author | Kahlert, Roland | |
dc.contributor.author | Liebeck, Matthias | |
dc.contributor.author | Cornelius, Joseph | |
dc.contributor.editor | Mitschang, Bernhard | |
dc.contributor.editor | Nicklas, Daniela | |
dc.contributor.editor | Leymann, Frank | |
dc.contributor.editor | Schöning, Harald | |
dc.contributor.editor | Herschel, Melanie | |
dc.contributor.editor | Teubner, Jens | |
dc.contributor.editor | Härder, Theo | |
dc.contributor.editor | Kopp, Oliver | |
dc.contributor.editor | Wieland, Matthias | |
dc.date.accessioned | 2017-06-21T11:24:42Z | |
dc.date.available | 2017-06-21T11:24:42Z | |
dc.date.issued | 2017 | |
dc.description.abstract | Many 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.identifier.isbn | 978-3-88579-660-2 | |
dc.identifier.pissn | 1617-5468 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-266 | |
dc.subject | Text Mining | |
dc.subject | Topic Recognition | |
dc.subject | Sentiment Analysis | |
dc.subject | Emotion Detection | |
dc.subject | ||
dc.title | Understanding Trending Topics in Twitter | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 384 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 375 | |
gi.conference.date | 6.-10. März 2017 | |
gi.conference.location | Stuttgart | |
gi.conference.sessiontitle | Studierendenprogramm |
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