Analysing user behaviour through dynamic population models

Higgs, M., Morrison, A., Girolami, M. and Chalmers, M. (2013) Analysing user behaviour through dynamic population models. In: CHI 2013: Extended Abstracts on Human Factors in Computing Systems, Paris, France, 27 Apr - 2 May 2013, pp. 271-276. ISBN 9781450319522 (doi:10.1145/2468356.2468405)

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Abstract

We apply a statistical modelling-based approach to exploring, analysing and predicting behavioural patterns of users of mobile software. The technique employed represents the behaviour of each user through a weighted mixture over data-generating distributions. In the described pilot study, we show how we have modelled the behaviour of over a hundred users of an iOS game. We illustrate how this modelling approach can be used to determine user play strategies and learning rates and show how this affects the length of time users keep returning to play the game. We describe our ongoing work, including feeding results of the modelling into the design process.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Chalmers, Professor Matthew and Higgs, Dr Matthew and Girolami, Prof Mark and Morrison, Dr Alistair
Authors: Higgs, M., Morrison, A., Girolami, M., and Chalmers, M.
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781450319522
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
566711A population approach to ubicomp system designMatthew ChalmersEngineering & Physical Sciences Research Council (EPSRC)EP/J007617/1COM - COMPUTING SCIENCE