Using social media mining for estimating theory of planned behaviour parameters
Marko Tkalcic (Johannes Kepler University Linz, University of Ljubljana)
Bruce Ferwerda (Johannes Kepler University Linz)
Markus Schedl (Johannes Kepler University Linz)
C.C.S. Liem (TU Delft - Multimedia Computing)
M.S. Melenhorst (TU Delft - Multimedia Computing)
Ante Odić (Outfit7 (Slovenian Subsidiary Ekipa2 D.o.o.))
Andrej Košir (University of Ljubljana)
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Abstract
In this position paper we present the scenario of making interventions for increasing the classical music concert-going behaviour of end users. Within the FP7 Phenicx project we are developing a personalized persuasive system that attempts at changing the concert-going behaviour of users. The system is based on the theory of planned behaviour user model for predicting whether a user will attend a concert or not. Our goal is to develop a machine learning algorithm that will extract the user model parameters unobtrusively from the micro-blogs of the users. We plan to perform a user study to build the training dataset and to test the system on real users within the project.
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