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dc.contributor.authorStojanovski, Darioen_US
dc.contributor.authorDimitrovski, Ivicaen_US
dc.contributor.authorMadjarov, Gjorgjien_US
dc.date.accessioned2022-09-27T13:01:57Z-
dc.date.available2022-09-27T13:01:57Z-
dc.date.issued2014-10-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/23135-
dc.description.abstractTwitter is the leading micro-blogging and social network service and is attracting an enormous amount of attention in recent years. Users on Twitter generate an abundance of information every day, establishing Twitter as the focal point for analyzing and visualizing social media data. In this paper, we present a web tool for visualizing Twitter data, TweetViz. TweetViz offers several different kinds of visualizations that can pertain to a Twitter user or any keyword or hashtag entered through the interface. TweetViz also includes a so called Streamgraph visualization that represents topic distribution in a set of tweets. The topic distributions are created using LDA (Latent Dirichlet Allocation).en_US
dc.relation.ispartofProceedings of the data mining and data warehousesen_US
dc.titleTweetviz: Twitter data visualizationen_US
dc.typeProceeding articleen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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