%0 Conference Paper %1 soap2017_surprise %A Bauer, Christine %A Schedl, Markus %B Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization %C New York, NY, USA %D 2017 %E Bieliková, Mária %E Herder, Eelco %E Cena, Federica %E Desmarais, Michel C. %I ACM %K %P 350-353 %R 10.1145/3099023.3099099 %T Introducing Surprise and Opposition by Design in Recommender Systems %U http://dblp.uni-trier.de/db/conf/um/umap2017a.html#BauerS17 %X There is a long tradition in recommender systems research to evaluate systems using quantitative performance measures on fixed datasets. As a reaction to this narrow accuracy-based focus in research, novel qualities beyond pure accuracy are emphasized in recent research; among them are surprise and opposition. This position paper considers that the perception of surprise and/or opposition may be purposely prepared when several recommendations are provided (e.g., in terms of a music playlist) or the user is given the choice between several options. Altering users' perception and triggering according behavior is well rooted in research on priming from psychology and nudge theory from the field of economic behavior. In this position paper, we propose how priming and nudging may be integrated into the design and evaluation of recommender systems to arouse surprise and opposition. %@ 978-1-4503-5067-9/17/07

@inproceedings{soap2017_surprise, abstract = {There is a long tradition in recommender systems research to evaluate systems using quantitative performance measures on fixed datasets. As a reaction to this narrow accuracy-based focus in research, novel qualities beyond pure accuracy are emphasized in recent research; among them are surprise and opposition. This position paper considers that the perception of surprise and/or opposition may be purposely prepared when several recommendations are provided (e.g., in terms of a music playlist) or the user is given the choice between several options. Altering users' perception and triggering according behavior is well rooted in research on priming from psychology and nudge theory from the field of economic behavior. In this position paper, we propose how priming and nudging may be integrated into the design and evaluation of recommender systems to arouse surprise and opposition.}, added-at = {2023-12-14T16:34:39.000+0100}, address = {New York, NY, USA}, author = {Bauer, Christine and Schedl, Markus}, biburl = {https://www.bibsonomy.org/bibtex/2c806889a1e0f2de42f7ded11857d2606/admin}, booktitle = {Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization}, doi = {10.1145/3099023.3099099}, editor = {Bieliková, Mária and Herder, Eelco and Cena, Federica and Desmarais, Michel C.}, eventdate = {9 July 2017}, eventtitle = {2nd Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems, in conjunction with 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017)}, interhash = {fa0c5d1d56772eaf0087705651361bbd}, intrahash = {c806889a1e0f2de42f7ded11857d2606}, isbn = {978-1-4503-5067-9/17/07}, keywords = {}, language = {English}, month = {July}, pages = {350-353}, publisher = {ACM}, series = {SOAP 2017}, timestamp = {2023-12-14T16:34:39.000+0100}, title = {Introducing Surprise and Opposition by Design in Recommender Systems}, type = {Conference Proceedings}, url = {http://dblp.uni-trier.de/db/conf/um/umap2017a.html#BauerS17}, venue = {Bratislava, Slovakia}, year = 2017 }