Constantinides, M;
Dowel, J;
Johnson, D;
Malacria, S;
(2015)
Habito News: A research tool to investigate mobile news reading.
In:
Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct.
(pp. p. 598).
ACM: New York, USA.
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Abstract
This demonstration paper accompanies a paper accepted at MobileHCI’15 [1]. With the aim of enhancing news reading experience on smartphones, we developed and deployed Habito News, a dedicated Android news app capable of unobtrusive logging of news interactions and recognising patterns of user’s news reading behaviour. Interaction traces collected with Habito News can first be used to detect the user’s news reader type and then to adapt the news reading app displays and behavior in response to individual patterns of user's interaction. In this demo, we present the app’s logging capabilities, the automatic detection of news reader types and the three different user interface designs for different news reader types.
Type: | Proceedings paper |
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Title: | Habito News: A research tool to investigate mobile news reading |
Event: | 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, August 24 - 27, 2015, Copenhagen, Denmark |
Location: | Copenhagen, Denmark |
ISBN-13: | 978-1-4503-3653-6 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1145/2786567.2792896 |
Publisher version: | http://dx.doi.org/10.1145/2786567.2792896 |
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: | News reading; News apps; Personalisation; Adaptive mobile user interfaces; |
UCL classification: | UCL UCL > Provost and Vice Provost Offices 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/1475070 |
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