Publication
Towards Predicting Hexad User Types from Smartphone Data
Maximilian Altmeyer; Pascal Lessel; Marc Schubhan; Antonio Krüger
In: Extended Abstracts of the 2019 Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium On Computer-Human Interaction in Play (CHI Play-2019), October 22-25, Barcelona, Spain, ISBN 978-1-4503-6871-1/19/10, ACM, 10/2019.
Abstract
Tailoring gamified systems has been shown to be appreciated
and more effective than “one-size-fits-all” systems. A
promising approach is using the Hexad user types model.
However, obtaining the Hexad user type requires users to
fill out a questionnaire, preventing an automated adaptation.
Since smartphone data was shown to be linked to personality
traits, which in turn were shown to be linked to the Hexad
user types, we explore to what extent it can be used to predict
the score of each user type. In our study (N=122) we
found regression models, indicating that using smartphone
data to predict user types is promising and may allow to
tailor gamified systems without explicit user interaction.