Empire 2013

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EMPIRE 2013 - 1st workshop on "Emotions and Personality in Personalized Services" http://empire2013.wordpress.com

in conjuction with UMAP 2013 (June 10-14, 2013 Rome, Italy)

While a lot of discussion has been made on filtering algorithms, and evaluation measures, few studies have stood to consider the role of emotions and personality in user models and personalized services. Characterizing the user model and the whole user experience with personalized service, by means of affective traits, is an important issue which merits attention from researchers and practitioners in both web technology and human factor fields.

Some questions motivate this workshop:

  • Do affective traits (personality, emotions, and mood) influence and determine the acceptance of the personalized suggestions?
  • How personality traits should be included in the user model?
  • How the personalized services should be adapted to emotions and mood to increase user satisfaction?


In the pursuit of increasing the quality of personalized services, researchers started to turn to more user-centric descriptors of content and services in recent years. The advances made in affective computing, especially in automatic emotion detection techniques, paved the way for the exploitation of emotions and personality as descriptors that account for a larger part of variance in user behavior than the generic descriptors (e.g. genre of a multimedia content) used so far.

Emotions, users' responses, can be characterized in different ways. The two most common approaches are (i) the discrete basic emotions (discrete classes, e.g. joy, sadness, fear, disgust, surprise, anger) and (ii) the continuous values, in the valence-arousal-dominance space. The affective computing community has been very active in the past decade and has developed several methods for the automatic non-invasive detection of emotions via several modalities (Zeng et al., 2009).

While emotions can change pretty quickly, personality, on the other hand, describes long-lasting human traits. The most common way of describing personality is the five-factor model (openness, conscientiousness, extraversion, agreeableness and neuroticism).

Emotions and personality in personalized services (e.g., recommender systems) can be exploited in different ways at different stages in the service-usage (e.g. content consumption) chain (Tkalčič et. al, 2011). In the entry stage they can be used as a contextual parameter, as additional information to predict, assist and influence decision-making (Kahneman, 2011) or a way to diversify the personalization via the detection of serendipitous services. In the consumption stage, emotions can be used as additional tags for the characterization of the services, content and users (Jiao and Pantid, 2011), opening new research areas for modeling services and content with different lengths. Finally, emotions can be exploited also for the non-invasive acquisition of the implicit user feedback as well as for novel evaluation metrics.

So far, research on emotions and personality in personalized services has been carried out in a scattered fashion. The goal of this workshop is to provide a venue for researchers to present their work, discuss it and benefit from the interaction.


  • Affective modeling
  • Emotions as context
  • Emotions in the decision-making process for recommender systems
  • Role of personality on user similarities
  • Emotion detection in recommended content consumption
  • Emotion detection as non-invasive feedback
  • Affective tagging of multimedia content and services
  • Emotion-based evaluation metrics (satisfaction...)
  • Lifestyle recommender systems
  • Personality and mood for group decision making
  • Incorporating personality and emotions in user models
  • Models based on personality
  • Datasets for affective modeling (Collecting, Available)
  • Personality traits acquisition (explicit vs. implicit)
  • Assessing personality traits implicitly from users’ activities/ratings/behavior
  • Personality and interfaces/control/bubble-control
  • Could interfaces/control/bubble-control be personalized based on personality traits? Should they be?
  • Personality and users’ tasks/goals
  • Do personality traits influence users’ goals?
  • Social signal processing for personalized services
  • Strategies for modeling emotions and personality
  • Recognizing triggers and causes of emotion
  • Theories about the relationship between reasoning and affect, between decision-making and affect
  • Methods for evaluating the utility of adaptation to affective factors


Two kinds of submissions are accepted:(i) full papers (up to 12 pages) and (ii) short papers (up to 6 pages). Submissions should be made through the EasyChair conference system:


and must adhere to the Springer LNCS format (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). All the submissions will be peer-reviewed. The accepted papers will be published in a centralized CEUR-WS volume of workshop papers and conference posters.

Further information can be found on the workshop's web page http://empire2013.wordpress.com


  • April, 1, 2013 Paper submission deadline
  • May, 1, 2013 Notification of acceptance
  • To Be Announced Workshop day


  • Marko Tkalčič, University of Ljubljana, Slovenia
  • Berardina De Carolis, University of Bari Aldo Moro, Italy
  • Marco de Gemmis, University of Bari Aldo Moro, Italy
  • Ante Odić, University of Ljubljana, Slovenia
  • Andrej Košir, University of Ljubljana, Slovenia

PROGRAM COMMITTEE (to be extended)

  • Alessandro Vinciarelli, University of Glasgow
  • Elisabeth Andre, Augsburg University
  • Floriana Grasso, Univ. Liverpool
  • Francesco Ricci, Free University of Bozen-Bolzano
  • Gustavo Gonzalez, http://goo.gl/tjDx0
  • Ioannis Arapakis, Yahoo! Barcelona
  • Jennifer Golbeck, University of Maryland
  • Judith Masthoff, University of Aberdeen
  • Li Chen, Hong Kong Baptist University
  • Man-Kwan Shan, National Chengchi University, Department of Computer Science
  • Marius Kaminskas, Free University of Bolzano
  • Martijn Willemsen, Eindhoven University of Technology, Netherlands
  • Markus Zanker, University Klagenfurt, Austria
  • Michal Kosinski, Microsoft
  • Mohammad Soleymani, Univ. Geneva/Imperial college
  • Neal Lathia, Cambridge University
  • Rong Hu , EPFL