4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE) 2016 Boston, MA, USA, September 16th, 2016 Proceedings edited by Marko Tkalčič Berardina de Carolis Marco de Gemmis Andrej Košir in conjunction with 10th ACM Conference on Recommender Systems (RecSys 2016) ii Preface This volume contains the papers presented at the 4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE), hold as part of the 10th ACM Conference on Recommender System (RecSys), in Boston, MA, USA. RecSys is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. Recommendation is a particular form of information filtering, that exploits past behaviors and user similarities to generate a list of information items that is personally tailored to an end-user’s preferences. The EMPIRE workshop focuses on the usage of psychologically-based constructs, such as emotions and personality, in delivering personalized content. The 9 (5 long, 4 short) technical papers included in the proceedings were selected through a rigorous reviewing process, where each paper was reviewed by three PC members. The EMPIRE chairs would like to thank the RecSys workshop chairs, Elizabeth Daly and Dietmar Jannach, for their guidance during the workshop organization. We also wish to thank all authors and all workshops participants for fruitful discussions, the members of the program committee and the external reviewers. All of them secured the workshop’s high quality standards. August 2016 Marko Tkalčič Berardina de Carolis Marco de Gemmis Andrej Košir iii iv EMPIRE 2016 Workshop Organization Chairs: Marko Tkalčič, Free University of Bozen-Bolzano, Italy Berardina De Carolis, University of Bari Aldo Moro, Italy Marco de Gemmis, University of Bari Aldo Moro, Italy Andrej Košir, University of Ljubljana, Slovenia Proceedings Chair: Marco de Gemmis, University of Bari Aldo Moro, Italy Web Chair: Marko Tkalčič, Free University of Bozen-Bolzano, Italy Program Committee: Ioannis Arapakis, Eurecat Matthias Braunhofer, Free University of Bozen-Bolzano Iván Cantador, Universidad Autónoma de Madrid Fabio Celli, University of Trento Li Chen, Hong Kong Baptist University Matt Dennis, University of Aberdeen Mehdi Elahi, Polytechnic University of Milan Bruce Ferwerda, Johannes Kepler University Sabine Graf, Athabasca University Peter Knees, Johannes Kepler University Fang-Fei Kuo, University of Washington Neal Lathia, University of Cambridge Matija Marolt, University of Ljubljana Fedelucio Narducci, University of Bari Aldo Moro Giuseppe Palestra, University of Bari Aldo Moro Viviana Patti, University of Turin Matevž Pesek, University of Ljubljana, Slovenia Marco Polignano, University of Bari Aldo Moro Olga C. Santos, aDeNu Research Group (UNED) Björn Schuller, University of Passau / Imperial College London Giovanni Semeraro, University of Bari Aldo Moro Man-Kwan Shan, National Chengchi University Yi-Hsuan Yang, Academia Sinica Martijn Willemsen, Eindhoven University of Technology Yong Zheng, DePaul University External Reviewer: Muhammad Anwar v vi Table of Contents Long Papers Adapt to Emotional Reactions In Context-aware Personalization 1-8 Yong Zheng Investigating the Role of Personality Traits and Influence Strategies on the Persuasive Effect of Personalized Recommendations 9-17 Sofia Gkika, Marianna Skiada, George Lekakos, Panos Kourouthanassis Personality in Computational Advertising: A Benchmark 18-25 Giorgio Roffo and Alessandro Vinciarelli Emotion Elicitation in Socially Intelligent Services: the Intelligent Typing Tutor Study Case 26-33 Andrej Košir, Marko Meža, Janja Košir, Matija Svetina, Gregor Strle Eliciting Emotions in Design of Games – a Theory Driven Approach 34-42 Alessandro Canossa, Jeremy Badler, Magy Seif El-Nasr, Eric Anderson Short Papers The Influence of Users’ Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists 43-47 Bruce Ferwerda, Mark Graus, Andreu Vall, Marko Tkalčič, Markus Schedl A Jungian based framework for Artificial Personality Synthesis 48-54 David Mascarenas A Comparative Analysis of Personality-Based Music Recommender Systems 55-59 Melissa Onori, Alessandro Micarelli, Giuseppe Sansonetti Recommender System Incorporating User Personality Profile through Analysis of Written Reviews 60-66 Peter Potash, Anna Rumshisky vii viii