Predicting Audience Engagement Across Social Media Platforms in the News Domain

Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen

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

Abstract

We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social media platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social media platform factors. Among other findings, results show that content with high engagement on one platform does not guarantee high engagement on another platform, even when news outlets use similar cross-platform posts; however, for some content, cross-sharing posts on a platform will increase overall audience engagement on another platform. As one of the few multiple social media platform studies, the findings have implications for the news domain, as well as other fields that distribute online content via social media.

Original languageEnglish
Title of host publicationSocial Informatics - 11th International Conference, SocInfo 2019, Proceedings
EditorsIngmar Weber, Kareem M. Darwish, Claudia Wagner, Claudia Wagner, Fabian Flöck, Emilio Zagheni, Samin Aref, Laura Nelson
PublisherSpringer
Pages173-187
Number of pages15
ISBN (Print)9783030349707
DOIs
Publication statusPublished - 1 Jan 2019
Event11th International Conference on Social Informatics, SocInfo 2019 - Doha, Qatar
Duration: 18 Nov 201921 Nov 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11864 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Social Informatics, SocInfo 2019
CountryQatar
CityDoha
Period18/11/1921/11/19

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Keywords

  • Audience engagement
  • News outlets
  • Social media

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Aldous, K. K., An, J., & Jansen, B. J. (2019). Predicting Audience Engagement Across Social Media Platforms in the News Domain. In I. Weber, K. M. Darwish, C. Wagner, C. Wagner, F. Flöck, E. Zagheni, S. Aref, & L. Nelson (Eds.), Social Informatics - 11th International Conference, SocInfo 2019, Proceedings (pp. 173-187). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11864 LNCS). Springer. https://doi.org/10.1007/978-3-030-34971-4_12