The Form of Content Personalisation at Mainstream, Transatlantic News Outlets: 2010–2016

ABSTRACT

In October 2016 the New York Times announced new content personalisation features for its websites and mobile apps, with the promise of “much more to come”. This article examines such developments via a quantitative content analysis of personalisation features at 15 major news outlets in the United Kingdom, the United States, and Germany and via interviews with senior editorial staff at some of those outlets. Both websites and mobile apps were studied, allowing comparisons to be made across platforms as well as geographically. Longitudinal comparisons were also made against an equivalent survey conducted in 2010. The results reveal significant changes over the last six years with, for example, rises in personalisation on mobile platforms, falls in the use of recommendations by friends, and convergence and commodification in content recommendation platforms. This study provides evidence to support continued debates on classical concerns such as selective exposure, but also raises new concerns about the effects of personalisation, including data protection and security issues.

KEYWORDS:

• Algorithmic journalism
• computational journalism
• content analysis
• customisation
• filter bubble
• mobile news
• news app
• personalisation

Acknowledgements

We would like to thank two anonymous reviewers for their valuable comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Neil Thurman http://orcid.org/0000-0003-3909-9565

Notes

1 Cordón García et al. (2013, 195–196) provide an extensive list of possible applications of personalisation.

2 Sørensen’s (2013) study was conducted between 2007 and 2011, and thus leaves out recent events.

Additional information

Funding

The work was supported by a research grant from the Volkswagen Foundation [grant number A110823/88171].