research-article

Observing Burstiness in Wikipedia Articles during New Disease Outbreaks

Authors:

Reham Al Tamime,

Richard Giordano,

Wendy HallAuthors Info & Claims

WebSci '18: Proceedings of the 10th ACM Conference on Web Science

Pages 117 - 126

https://doi.org/10.1145/3201064.3201080

Published: 15 May 2018 Publication History

Abstract

Wikipedia can be conceptualized as an open sociotechnical environment that supports communities of humans and bots that update and contest information in Wikipedia articles. This environment affords a view to community or domain interactions and reactions to salient topics, such as disease outbreaks. But do reactions to different topics vary, and how can we measure them? One widely-used approach when answering these questions is to delineate levels of burstiness-communication flows characterized by repeated bursts instead of a continuous stream-in the construction of a Wikipedia article. A literature review, however, reveals that current burstiness approaches do not fully support efforts to compare Wikipedia community reactions to different articles. Through an empirical analysis of the construction of Wikipedia health-related articles, we both extend and refine burstiness as an analytical technique to understand the community dynamics underlying the construction of Wikipedia articles. We define a method by which we can categorize burstiness as high medium and low. Our empirical results suggest a proposed a model of burstiness.

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Li ZHu HWang HCai LZhang HZhang K(2022)Why does the president tweet this? Discovering reasons and contexts for politicians’ tweets from news articlesInformation Processing and Management: an International Journal10.1016/j.ipm.2022.10289259:3Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.ipm.2022.102892
Ruprechter THorta Ribeiro MSantos TLemmerich FStrohmaier MWest RHelic D(2021)Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictionsScientific Reports10.1038/s41598-021-00789-311:1Online publication date: 2-Nov-2021
https://doi.org/10.1038/s41598-021-00789-3
Fisichella M(2021)Unified approach to retrospective event detection for event- based epidemic intelligenceInternational Journal on Digital Libraries10.1007/s00799-021-00308-9Online publication date: 9-Oct-2021
https://doi.org/10.1007/s00799-021-00308-9
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Index Terms

Observing Burstiness in Wikipedia Articles during New Disease Outbreaks
1. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools
      1. Wikis

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cover image ACM Conferences

WebSci '18: Proceedings of the 10th ACM Conference on Web Science

May 2018

399 pages

ISBN:9781450355636

DOI:10.1145/3201064

General Chairs:
Hans Akkermans
Vrije Universiteit Amsterdam, The Netherlands
,
Kathy Fontaine
Rensselaer Polytechnic Institute, USA
,
Ivar Vermeulen
Vrije Universiteit Amsterdam, The Netherlands
,
Program Chairs:
Geert-Jan Houben
TU Delft, The Netherlands
,
Matthew S. Weber
Rutgers University, New Jersey, USA

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Published: 15 May 2018

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EPSRC Centre for Doctoral Training in Web Science Innovation
Qatar Foundation

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WebSci '18

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WebSci '18: 10th ACM Conference on Web Science

May 27 - 30, 2018

Amsterdam, Netherlands

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WebSci '18 Paper Acceptance Rate 30 of 113 submissions, 27%;

Overall Acceptance Rate 245 of 933 submissions, 26%

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Cited By

Li ZHu HWang HCai LZhang HZhang K(2022)Why does the president tweet this? Discovering reasons and contexts for politicians’ tweets from news articlesInformation Processing and Management: an International Journal10.1016/j.ipm.2022.10289259:3Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.ipm.2022.102892
Ruprechter THorta Ribeiro MSantos TLemmerich FStrohmaier MWest RHelic D(2021)Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictionsScientific Reports10.1038/s41598-021-00789-311:1Online publication date: 2-Nov-2021
https://doi.org/10.1038/s41598-021-00789-3
Fisichella M(2021)Unified approach to retrospective event detection for event- based epidemic intelligenceInternational Journal on Digital Libraries10.1007/s00799-021-00308-9Online publication date: 9-Oct-2021
https://doi.org/10.1007/s00799-021-00308-9
DOĞANER A(2020)The Role of Wikipedia in providing information on coronavirus to Societies during the COVID-19 PandemicMiddle Black Sea Journal of Health Science10.19127/mbsjohs.7819306:3(316-324)Online publication date: 31-Dec-2020
https://doi.org/10.19127/mbsjohs.781930
Kushner TSharma A(2020)Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health ForumsProceedings of The Web Conference 202010.1145/3366423.3380056(2906-2912)Online publication date: 20-Apr-2020
https://dl.acm.org/doi/10.1145/3366423.3380056
Tahir FAbdullah MBukhari FAlmustafa KIqbal W(2020)Online Workload Burst Detection for Efficient Predictive Autoscaling of ApplicationsIEEE Access10.1109/ACCESS.2020.29882078(73730-73745)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2988207
Chen ZIwaihara M(2020)Detection of Editing Bursts and Extraction of Significant Keyphrases from Wikipedia Edit HistoryBig Data Analyses, Services, and Smart Data10.1007/978-981-15-8731-3_4(45-65)Online publication date: 11-Sep-2020
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Dooley PBožić B(2019)Towards Linked Data for Wikidata Revisions and Twitter Trending HashtagsProceedings of the 21st International Conference on Information Integration and Web-based Applications & Services10.1145/3366030.3366048(166-175)Online publication date: 2-Dec-2019
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Reeves NSimperl E(2019)Efficient, but Effective?Proceedings of the ACM on Human-Computer Interaction10.1145/33592793:CSCW(1-35)Online publication date: 7-Nov-2019
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Chen ZIwaihara M(2019)Detection of Bursty and Significant Keyphrases from Wikipedia edit history2019 IEEE International Conference on Big Data and Smart Computing (BigComp)10.1109/BIGCOMP.2019.8679105(1-4)Online publication date: Feb-2019
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