Headlines Matter: Using Headlines to Predict the Popularity of News Articles on Twitter and Facebook

Piotrkowicz, A orcid.org/0000-0002-7723-699X, Dimitrova, VG orcid.org/0000-0002-7001-0891, Otterbacher, J et al. (1 more author) (2017) Headlines Matter: Using Headlines to Predict the Popularity of News Articles on Twitter and Facebook. In: Proceedings of the Eleventh International AAAI Conference on Web and Social Media (ICWSM 2017). 11th International AAAI Conference on Web and Social Media (ICWSM-17), 15-18 May 2017, Montreal, Canada. Association for the Advancement of Artificial Intelligence , pp. 656-659. ISBN 978-1-57735-788-9

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Keywords: text analytics; prediction models; social media popularity; news headlines
Dates:
  • Accepted: 1 March 2017
  • Published: 15 May 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 13 Apr 2017 10:02
Last Modified: 19 Aug 2024 12:11
Published Version: https://ojs.aaai.org/index.php/ICWSM/article/view/...
Status: Published
Publisher: Association for the Advancement of Artificial Intelligence
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Open Archives Initiative ID (OAI ID):

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