Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2022
Abstract
This research characterises user engagement of approximately 3,000,000 news postings of 53 news outlets and 50,000,000 associated user comments during 8 months on 5 social media platforms (i.e. Facebook, Instagram, Twitter, YouTube, and Reddit). We investigate the effect of sentiments and topics on user engagement across four levels of user engagement expressions (i.e. views, likes, comments, cross-platform posting). We find that sentiments and topics differ by both news outlets and social media platforms, and both sentiments and topics by the four levels of user engagement expression. Finally, we predict a volume of four user engagement levels for given news content, with an 83% maximum average F1-score for the external posting of news articles from one platform to another using language and metadata features. Implications are that news outlets can benefit by developing a platform, sentiment and topic, and strategies to best achieve user engagement objectives.
Keywords
User engagement, cross platforms, news organisation;, opical analysis, sentiment analysis, social media
Discipline
Communication Technology and New Media | Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Publication
Behaviour & Information Technology
Volume
42
Issue
5
First Page
545
Last Page
568
ISSN
0144-929X
Identifier
10.1080/0144929X.2022.2030798
Publisher
Taylor and Francis Group
Citation
ALDOUS, Kholoud K.; AN, Jisun; and JANSEN, Bernard J..
What really matters?: Characterising and predicting user engagement of news postings using multiple platforms, sentiments and topics. (2022). Behaviour & Information Technology. 42, (5), 545-568.
Available at: https://ink.library.smu.edu.sg/sis_research/9853
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/0144929X.2022.2030798
Included in
Communication Technology and New Media Commons, Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons