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Exploring mobile news reading interactions for news app personalisation

Constantinides, M; Dowell, J; Johnson, D; Malacria, S; (2015) Exploring mobile news reading interactions for news app personalisation. In: Boring, S and Rukzio, E and Gellersen, H and Hinckley, K, (eds.) Mobile HCI'15: Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. (pp. pp. 457-462). Association for Computing Machinery: Copenhagen, Denmark. Green open access

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Abstract

As news is increasingly accessed on smartphones and tablets, the need for personalising news app interactions is apparent. We report a series of three studies addressing key issues in the development of adaptive news app interfaces. We first surveyed users' news reading preferences and behaviours; analysis revealed three primary types of reader. We then implemented and deployed an Android news app that logs users' interactions with the app. We used the logs to train a classifier and showed that it is able to reliably recognise a user according to their reader type. Finally we evaluated alternative, adaptive user interfaces for each reader type. The evaluation demonstrates the differential benefit of the adaptation for different users of the news app and the feasibility of adaptive interfaces for news apps.

Type: Proceedings paper
Title: Exploring mobile news reading interactions for news app personalisation
Event: 17th International Conference on Human-Computer Interaction with Mobile Devices and Services (Mobile HCI'15)
Location: Copenhagen, Denmark
ISBN-13: 9781450336529
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2785830.2785860
Publisher version: http://dx.doi.org/10.1145/2785830.2785860
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Mobile news reading, personalisation, implicit sampling, adaptive mobile user interfaces.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1475069
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