What really matters?: characterising and predicting user engagement of news postings using multiple platforms, sentiments and topics. Issue 5 (4th April 2023)

• Record Type: Journal Article
• Authors: Aldous, Kholoud Khalil; An, Jisun; Jansen, Bernard J.
• Is Part Of: Behaviour & information technology. Volume 42:Issue 5(2023)
• Page Start: 545
• Page End: 568
• Publication Date: 2023-04-04
• Subjects: User engagement -- cross platforms -- news organisation -- topical analysis -- sentiment analysis -- social media; Electronic data processing -- Periodicals; Human engineering -- Periodicals; Information technology -- Periodicals; 303.4833
• DOI: 10.1080/0144929X.2022.2030798
• Languages: English
• ISSNs: 0144-929X

Abstract

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.