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dc.contributor.authorBurnap, Pete
dc.contributor.authorWilliams, Matthew L.
dc.contributor.authorSloan, Luke
dc.contributor.authorRana, Omer
dc.contributor.authorHousley, William
dc.contributor.authorEdwards, Adam
dc.contributor.authorKnight, Vincent
dc.contributor.authorProcter, Rob
dc.contributor.authorVoss, Alexander
dc.date.accessioned2015-07-10T12:10:03Z
dc.date.available2015-07-10T12:10:03Z
dc.date.issued2014-06
dc.identifier.citationBurnap , P , Williams , M L , Sloan , L , Rana , O , Housley , W , Edwards , A , Knight , V , Procter , R & Voss , A 2014 , ' Tweeting the terror : modelling the social media reaction to the Woolwich terrorist attack ' , Social Network Analysis and Mining , vol. 4 , no. 1 , 206 . https://doi.org/10.1007/s13278-014-0206-4en
dc.identifier.issn1869-5450
dc.identifier.otherPURE: 192237798
dc.identifier.otherPURE UUID: e4fec9d3-2469-4469-a7c2-a9ebcf1064cb
dc.identifier.otherBibtex: urn:839a9f3241c100bdcaa3024a2ced708f
dc.identifier.otherScopus: 84906264962
dc.identifier.otherORCID: /0000-0002-8053-2175/work/31093299
dc.identifier.urihttp://hdl.handle.net/10023/6962
dc.descriptionDate of Acceptance: 23/05/2014en
dc.description.abstractLittle is currently known about the factors that promote the propagation of information in online social networks following terrorist events. In this paper we took the case of the terrorist event in Woolwich, London in 2013 and built models to predict information flow size and survival using data derived from the popular social networking site Twitter. We define information flows as the propagation over time of information posted to Twitter via the action of retweeting. Following a comparison with different predictive methods, and due to the distribution exhibited by our dependent size measure, we used the zerotruncated negative binomial (ZTNB) regression method. To model survival, the Cox regression technique was used because it estimates proportional hazard rates for independent measures. Following a principal component analysis to reduce the dimensionality of the data, social, temporal and content factors of the tweet were used as predictors in both models. Given the likely emotive
dc.format.extent14
dc.language.isoeng
dc.relation.ispartofSocial Network Analysis and Miningen
dc.rightsCopyright The Author(s) 2014. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.en
dc.subjectSocial network analysisen
dc.subjectTwitteren
dc.subjectInformation flowsen
dc.subjectInformation propagationen
dc.subjectInformation spreadingen
dc.subjectSocial mediaen
dc.subjectSentiment analysisen
dc.subjectOpinion miningen
dc.subjectPredictive modelsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectH Social Sciencesen
dc.subject.lccQA75en
dc.subject.lccHen
dc.titleTweeting the terror : modelling the social media reaction to the Woolwich terrorist attacken
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1007/s13278-014-0206-4
dc.description.statusPeer revieweden


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