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Tweeting the terror : modelling the social media reaction to the Woolwich terrorist attack

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burnap2014socnetwanalmin206.pdf (568.9Kb)
Date
06/2014
Author
Burnap, Pete
Williams, Matthew L.
Sloan, Luke
Rana, Omer
Housley, William
Edwards, Adam
Knight, Vincent
Procter, Rob
Voss, Alexander
Keywords
Social network analysis
Twitter
Information flows
Information propagation
Information spreading
Social media
Sentiment analysis
Opinion mining
Predictive models
QA75 Electronic computers. Computer science
H Social Sciences
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Abstract
Little 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
Citation
Burnap , 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/s13278-014-0206-4
Publication
Social Network Analysis and Mining
Status
Peer reviewed
DOI
https://doi.org/10.1007/s13278-014-0206-4
ISSN
1869-5450
Type
Journal article
Rights
Copyright 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.
Description
Date of Acceptance: 23/05/2014
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/6962

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