TY - GEN
T1 - Predicting Audience Engagement Across Social Media Platforms in the News Domain
AU - Aldous, Kholoud Khalil
AU - An, Jisun
AU - Jansen, Bernard J.
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Audience engagement
KW - News outlets
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85076723968&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-34971-4_12
DO - 10.1007/978-3-030-34971-4_12
M3 - Conference contribution
AN - SCOPUS:85076723968
SN - 9783030349707
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 173
EP - 187
BT - Social Informatics - 11th International Conference, SocInfo 2019, Proceedings
A2 - Weber, Ingmar
A2 - Darwish, Kareem M.
A2 - Wagner, Claudia
A2 - Wagner, Claudia
A2 - Flöck, Fabian
A2 - Zagheni, Emilio
A2 - Aref, Samin
A2 - Nelson, Laura
PB - Springer
T2 - 11th International Conference on Social Informatics, SocInfo 2019
Y2 - 18 November 2019 through 21 November 2019
ER -