Tracking online topics over time: Understanding dynamic hashtag communities

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dc.contributor.authorLorenz-Spreen, Philipp
dc.contributor.authorWolf, Frederik
dc.contributor.authorBraun, Jonas
dc.contributor.authorGhoshal, Gourab
dc.contributor.authorDjurdjevac Conrad, Nataša
dc.contributor.authorHövel, Philipp
dc.date.accessioned2019-10-02T04:36:01Z
dc.date.available2019-10-02T04:36:01Z
dc.date.issued2018-10-19
dc.description.abstractHashtags are widely used for communication in online media. As a condensed version of information, they characterize topics and discussions. For their analysis, we apply methods from network science and propose novel tools for tracing their dynamics in time-dependent data. The observations are characterized by bursty behaviors in the increases and decreases of hashtag usage. These features can be reproduced with a novel model of dynamic rankings.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid9en
dc.identifier.citationLorenz-Spreen, P., Wolf, F., Braun, J., Ghoshal, G., Conrad, N.D. and Hövel, P., 2018. Tracking online topics over time: understanding dynamic hashtag communities. Computational social networks, 5(1), 9 (18pp.). DOI:10.1186/s40649-018-0058-6en
dc.identifier.doi10.1186/s40649-018-0058-6en
dc.identifier.eissn2197-4314
dc.identifier.endpage18en
dc.identifier.issued1en
dc.identifier.journaltitleComputational Social Networksen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/8657
dc.identifier.volume5en
dc.language.isoenen
dc.publisherSpringer Openen
dc.relation.urihttps://computationalsocialnetworks.springeropen.com/articles/10.1186/s40649-018-0058-6
dc.rights© The Author(s) 2018, This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectOnline mediaen
dc.subjectHashtagsen
dc.subjectTemporal community detectionen
dc.subjectRandom walken
dc.subjectMemory matchingen
dc.subjectTopic dynamicsen
dc.subjectRankingen
dc.subjectAging modelen
dc.subjectBurstsen
dc.titleTracking online topics over time: Understanding dynamic hashtag communitiesen
dc.typeArticle (peer-reviewed)en
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