Using social media mining for estimating theory of planned behaviour parameters

Marko Tkalcic; Bruce Ferwerda; Markus Schedl; C.C.S. Liem; Mark Melenhorst; Ante Odic; A. Kosir

Using social media mining for estimating theory of planned behaviour parameters

Marko Tkalcic, Bruce Ferwerda, Markus Schedl, C.C.S. Liem, Mark Melenhorst, Ante Odic, A. Kosir

Institute of Computational Perception

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

In this position paper we present the scenario of making in- terventions for increasing the classical music concert-going behaviour of end users. Within the FP7 Phenicx project we are developing a person- alized persuasive system that attempts at changing the concert-going behaviour of users. The system is based on the theory of planned be- haviour user model for predicting whether a user will attend a concert or not. Our goal is to develop a machine learning algorithm that will ex- tract 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.

Original language	English
Title of host publication	Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE), at the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP) , Aalborg, Denmark
Number of pages	8
Publication status	Published - 2014

Fields of science

202002 Audiovisual media
102 Computer Sciences
102001 Artificial intelligence
102003 Image processing
102015 Information systems

JKU Focus areas

Computation in Informatics and Mathematics
Engineering and Natural Sciences (in general)

Cite this

Tkalcic, M., Ferwerda, B., Schedl, M., Liem, C. C. S., Melenhorst, M., Odic, A., & Kosir, A. (2014). Using social media mining for estimating theory of planned behaviour parameters. In Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE), at the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP) , Aalborg, Denmark

@inproceedings{17e9986e01b44b2aa99d6db9b7fdeb87,

title = "Using social media mining for estimating theory of planned behaviour parameters",

abstract = "In this position paper we present the scenario of making in- terventions for increasing the classical music concert-going behaviour of end users. Within the FP7 Phenicx project we are developing a person- alized persuasive system that attempts at changing the concert-going behaviour of users. The system is based on the theory of planned be- haviour user model for predicting whether a user will attend a concert or not. Our goal is to develop a machine learning algorithm that will ex- tract 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.",

author = "Marko Tkalcic and Bruce Ferwerda and Markus Schedl and C.C.S. Liem and Mark Melenhorst and Ante Odic and A. Kosir",

year = "2014",

language = "English",

booktitle = "Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE), at the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP) , Aalborg, Denmark",

}

Using social media mining for estimating theory of planned behaviour parameters. / Tkalcic, Marko; Ferwerda, Bruce; Schedl, Markus et al.
Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE), at the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP) , Aalborg, Denmark. 2014.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - Using social media mining for estimating theory of planned behaviour parameters

AU - Tkalcic, Marko

AU - Ferwerda, Bruce

AU - Schedl, Markus

AU - Liem, C.C.S.

AU - Melenhorst, Mark

AU - Odic, Ante

AU - Kosir, A.

PY - 2014

Y1 - 2014

N2 - In this position paper we present the scenario of making in- terventions for increasing the classical music concert-going behaviour of end users. Within the FP7 Phenicx project we are developing a person- alized persuasive system that attempts at changing the concert-going behaviour of users. The system is based on the theory of planned be- haviour user model for predicting whether a user will attend a concert or not. Our goal is to develop a machine learning algorithm that will ex- tract 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.

AB - In this position paper we present the scenario of making in- terventions for increasing the classical music concert-going behaviour of end users. Within the FP7 Phenicx project we are developing a person- alized persuasive system that attempts at changing the concert-going behaviour of users. The system is based on the theory of planned be- haviour user model for predicting whether a user will attend a concert or not. Our goal is to develop a machine learning algorithm that will ex- tract 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.

M3 - Conference proceedings

BT - Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE), at the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP) , Aalborg, Denmark

ER -