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Exploring mobile news reading interactions for news app personalisation

Constantinides, M ; Dowell, J ; Johnson, D ; Malacria, S

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Título:
Exploring mobile news reading interactions for news app personalisation
Autor: Constantinides, M ; Dowell, J ; Johnson, D ; Malacria, S
Assuntos: adaptive mobile user interfaces ; implicit sampling ; Mobile news reading ; personalisation
Notas: 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. (2015)
Descrição: 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.
Editor: Association for Computing Machinery
Data de criação/publicação: 2015
Idioma: Inglês

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