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Behavioural Analysis of Mobile Web Users

Author(s)
Albatal, Rami  
Briggs, Peter  
Coyle, Maurice  
Gavarini, Sebastian  
Tomin, Johannes  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/8405
Date Issued
2016-05-27
Date Available
2017-03-28T15:52:47Z
Abstract
As smartphones become the predominant devices for accessing the web, understanding how individuals express their interests and interact with the web can have a great impact on several domains ranging from customer services to marketing and public policy. However, in order to better understand the web surfing behaviour and interests of mobile network subscribers, we need to look beyond the classic analytics that are based on location, internet usage and social networks. A more granular view of user behaviour and interests can be achieved by including more advanced analytics based on the content that the users are engaging with. In this paper we present a novel mobile web content analytics platform, HeyStaks, with the goal of filling the gap of granular content analysis for mobile user behavioural analytics.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
School of Computing, Dublin City University, The Insight Centre for Data Analytics, the University of Aberdeen and Noldus
Start Page
123
End Page
129
Subjects

Recommender systems

Web versions
http://www.measuringbehavior.org/mb2016/home
Language
English
Status of Item
Peer reviewed
Journal
Sprink, A., Riedel, G., Zhou, L., Teekens, L., Albatal, R. and Gurrin, C. (eds.). Proceedings of Measuring Behavior 2016: 10th International Conference on Methods and Techniques in Behavioral Research
Conference Details
Measuring Behavior 2016: 10th International Conference on Methods and Techniques in Behavioral Research, Dublin, Ireland, 25-27 May 2016
ISBN
9781873769591
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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insight_publication.pdf

Size

437.28 KB

Format

Adobe PDF

Checksum (MD5)

ea8632834af511d63eb366e0c21288f0

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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