Characterizing the life cycle of online news stories using social media reactions

Carlos Castillo, Mohammed El-Haddad, Jürgen Pfeffer, Matt Stempeck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

69 Citations (Scopus)

Abstract

This paper presents a study of the life cycle of news articles posted online. We describe the interplay between website visitation patterns and social media reactions to news content. We show that we can use this hybrid observation method to characterize distinct classes of articles. We also find that social media reactions can help predict future visitation patterns early and accurately. We validate our methods using qualitative analysis as well as quantitative analysis on data from a large international news network, for a set of articles generating more than 3,000,000 visits and 200,000 social media reactions. We show that it is possible to model accurately the overall traffic articles will ultimately receive by observing the first ten to twenty minutes of social media reactions. Achieving the same prediction accuracy with visits alone would require to wait for three hours of data. We also describe significant improvements on the accuracy of the early prediction of shelf-life for news stories.

Original languageEnglish
Title of host publicationProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
PublisherAssociation for Computing Machinery
Pages211-223
Number of pages13
ISBN (Print)9781450325400
DOIs
Publication statusPublished - 1 Jan 2014
Event17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014 - Baltimore, MD, United States
Duration: 15 Feb 201419 Feb 2014

Other

Other17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014
CountryUnited States
CityBaltimore, MD
Period15/2/1419/2/14

Fingerprint

Life cycle
Websites
Chemical analysis

Keywords

  • Online news
  • Predictive web analytics
  • Web analytics

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

Castillo, C., El-Haddad, M., Pfeffer, J., & Stempeck, M. (2014). Characterizing the life cycle of online news stories using social media reactions. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (pp. 211-223). Association for Computing Machinery. https://doi.org/10.1145/2531602.2531623

Characterizing the life cycle of online news stories using social media reactions. / Castillo, Carlos; El-Haddad, Mohammed; Pfeffer, Jürgen; Stempeck, Matt.

Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, 2014. p. 211-223.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Castillo, C, El-Haddad, M, Pfeffer, J & Stempeck, M 2014, Characterizing the life cycle of online news stories using social media reactions. in Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, pp. 211-223, 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014, Baltimore, MD, United States, 15/2/14. https://doi.org/10.1145/2531602.2531623
Castillo C, El-Haddad M, Pfeffer J, Stempeck M. Characterizing the life cycle of online news stories using social media reactions. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery. 2014. p. 211-223 https://doi.org/10.1145/2531602.2531623
Castillo, Carlos ; El-Haddad, Mohammed ; Pfeffer, Jürgen ; Stempeck, Matt. / Characterizing the life cycle of online news stories using social media reactions. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, 2014. pp. 211-223
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