Article

Hashtag lifespan and social networks during the london riots

Authors:

Kimberly Glasgow,

Clayton FinkAuthors Info & Claims

SBP'13: Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction

Pages 311 - 320

https://doi.org/10.1007/978-3-642-37210-0_34

Published: 02 April 2013 Publication History

Abstract

Social media is a powerful medium for rapidly sharing information and organizing response in times of crisis or extreme events. Twitter users have adopted a convention of hashtags to support this and other uses of microblogging services. Using Twitter data from the 2011 London riots, we analyze emergent social networks directly relating to response to crisis. We examine networks of riot response oriented around cleanup or prayer activities. These networks differ in size, structure, general membership, and prominent actors. We explore whether temporal patterns observed in social media, such as hashtag "lifespan," may relate to observed social processes and behaviors.

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Cited By

Tsvetkova MYasseri TMeyer EPickering JEngen VWalland PLüders MFølstad ABravos G(2017)Understanding Human-Machine NetworksACM Computing Surveys10.1145/303986850:1(1-35)Online publication date: 4-Apr-2017
https://dl.acm.org/doi/10.1145/3039868
Liu ZHuang YTrampier JAli MNewsam SRenz MTrajcevski GRavada S(2016)Spatiotemporal topic association detection on tweetsProceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/2996913.2996933(1-10)Online publication date: 31-Oct-2016
https://dl.acm.org/doi/10.1145/2996913.2996933
Glasgow KVitak JTausczik YFink C(2016)Grieving in the 21st CenturyProceedings of the 7th 2016 International Conference on Social Media & Society10.1145/2930971.2930975(1-10)Online publication date: 11-Jul-2016
https://dl.acm.org/doi/10.1145/2930971.2930975
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Published In

cover image Guide Proceedings

SBP'13: Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction

April 2013

532 pages

ISBN:9783642372094

Editors:
Ariel M. Greenberg
Applied Physics Laboratory, Research and Exploratory Development Department, Johns Hopkins University, 11100 Johns Hopkins Road, Laurel, MD
,
William G. Kennedy
Center for Social Complexity, Department of Computational Social Science, Krasnow Institute for Advanced Study, George Mason University, 4400 University Drive, Fairfax, VA
,
Nathan D. Bos
Applied Physics Laboratory, Research and Exploratory Development Department, Johns Hopkins University, 11100 Johns Hopkins Road, Laurel, MD

Sponsors

The U.S. Army Research Office: The U.S. Army Research Office
National Institutes of Health: National Institutes of Health
Office of Naval Research
The National Science Foundation

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 02 April 2013

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Cited By

Tsvetkova MYasseri TMeyer EPickering JEngen VWalland PLüders MFølstad ABravos G(2017)Understanding Human-Machine NetworksACM Computing Surveys10.1145/303986850:1(1-35)Online publication date: 4-Apr-2017
https://dl.acm.org/doi/10.1145/3039868
Liu ZHuang YTrampier JAli MNewsam SRenz MTrajcevski GRavada S(2016)Spatiotemporal topic association detection on tweetsProceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/2996913.2996933(1-10)Online publication date: 31-Oct-2016
https://dl.acm.org/doi/10.1145/2996913.2996933
Glasgow KVitak JTausczik YFink C(2016)Grieving in the 21st CenturyProceedings of the 7th 2016 International Conference on Social Media & Society10.1145/2930971.2930975(1-10)Online publication date: 11-Jul-2016
https://dl.acm.org/doi/10.1145/2930971.2930975
Fairbanks JKannan RPark HBader D(2015)Behavioral clusters in dynamic graphsParallel Computing10.1016/j.parco.2015.03.00247:C(38-50)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1016/j.parco.2015.03.002
Fairbanks JEdiger DMcColl RBader DGilbert ERokne JFaloutsos C(2013)A statistical framework for streaming graph analysisProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/2492517.2492620(341-347)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1145/2492517.2492620

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