[agents] UMUAI Special Issue on Personality in Personalized Systems - final cfp

[Marko Tkalcic]

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FINAL CALL FOR PAPERS

Special Issue on Personality in Personalized Systems

User Modeling and User-Adapted Interaction:
The Journal of Personalization Research (UMUAI)

*** Extended abstract submission deadline: December 1, 2014
*** Paper submission deadline (for accepted abstracts): March 1, 2015
Special Issue Web site: 
http://www.cp.jku.at/people/tkalcic/umuai_personality.html
UMUAI Web site: http://www.umuai.org/

GUEST EDITORS:
- Marko Tkalčič, Johannes Kepler University, Linz, Austria, 
marko.tkalcic at jku.at
- Daniele Quercia, Yahoo Labs, Barcelona, Spain, dquercia at yahoo-inc.com
- Sabine Graf, Athabasca University, Edmonton, Canada , 
sabineg at athabascau.ca
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SCOPE OF THE SPECIAL ISSUE

Personality has been found to correlate with a number of real-world 
behaviors. For example, it correlates with musical taste: popular music 
tends to be liked by extroverts, whereas people with a tendency to be 
less open to experience tend to prefer religious music and to dislike 
rock music. Personality also impacts on the forming of social relations: 
friends tend to be, to a very similar extent, open to experience and 
extrovert. Furthermore, there is a strong correlation between 
personality and how people prefer to learn, indicating that learning 
styles can be seen as a subset of personality. Since personality has 
been shown to affect real-world user preferences (e.g. preferences for 
interaction styles, preferences for learning, preferences for musical 
genres), we might conclude that the design of online services (e.g., 
personalized user interfaces, music recommender systems, adaptive 
educational systems, and games) might also benefit from personality studies.

This is the reason why researchers have recently explored the extent to 
which personality traits impact on the use of interactive and hypermedia 
systems. They found, for example, that personality is associated with 
specific preferences for music genres online, and that this greatly 
impacts on music-information retrieval services. Collaborative filtering 
techniques have also benefited from assessing the users’ personality 
traits. It has also been shown that users open to new experiences (one 
of the big five personality traits) tend to prefer more diverse and 
serendipitous items (e.g., movies). Furthermore, learning styles have 
been heavily used in educational systems to personalize courses in terms 
of the structure and presentation of learning materials. In the context 
of games, for example, it has been found that personality seems to 
impact on the motivation for playing online games. Also, certain 
personality traits have been found to correlate with communication 
styles and, as a consequence, the adoption of location-sharing social media.

The five-factor model of personality, or the Big Five, is the most 
commonly used set of personality concepts and one of the most reliable 
and comprehensive models of personality. In this model, an individual is 
associated with five scores that correspond to the five main personality 
traits. The names of those traits form the acronym OCEAN: Openness, 
Conscientiousness, Extraversion, Agreeableness, and Neuroticism.

Other models of personality are, for example, the Four Temperaments (the 
oldest general model), the Benziger brain type (a work-related model), 
the Belbin team roles model, the Myers-Briggs types (general and 
team-working model), the RIASEC vocational model or the Bartle types 
(describing personalities in video games).

While personality traits are normally identified by asking people to 
complete a questionnaire, researchers have recently shown that 
personality traits can be extracted implicitly from the users' streams 
(e.g., tweets, Facebook updates) without resorting to time-consuming 
questionnaires. Furthermore, players’ behaviors in games have been 
investigated and can also provide information about a player’s 
personality. Similarly, several researchers have conducted studies on 
using data from learners’ behaviors in a course to automatically 
identify their learning styles.


TOPICS

The topics of interest for this special issue include (but are not 
limited to):
* Personality models for personalized systems;
* Personality prediction/extraction/assessment from behavior and/or 
preference data in
    * games
    * multimedia content (e.g., music, films, etc.)
    * social media
    * educational systems
    * business applications
    * other modalities (e.g., mobile devices etc.)
* Automatic prediction/extraction/assessment of other (e.g., lower-level 
or application- specific)  personality factors such as
    * learning styles
    * cognitive styles
    * communication styles
    * thinking styles
* Privacy issues;
* Enhancing user/learner models with personality;
* Evaluation of personality-based personalized services;
* Novel applications considering personality including
    * personality in games
    * personality and learning styles in educational systems
    * personality and multimedia content
    * personality in social media
    * personality and recommender systems


PAPER SUBMISSION & REVIEW PROCESS

The prospective authors must first submit an extended abstract of no 
more than 4 single-spaced pages, formatted with 12-pt font and 1-inch 
margins, through easychair:

https://www.easychair.org/conferences/?conf=umuai-personality-20

by December 1, 2014. This abstract should be preceded by a completed 
UMUAI self-assessment form that can be found at 
http://www.umuai.org/self-assessment.html, preferably both in a single 
PDF file.

All submitted abstracts will receive an initial screening by the editors 
of the special issue.  The authors of the abstracts will be notified 
about the results of the initial screening by *** December 15, 2014 
***.  Abstracts that do not pass this initial screening (i.e., the 
abstracts that are deemed not to have a reasonable chance of acceptance) 
will not be considered further.

Authors of abstracts that pass the initial screening will be invited to 
submit the full version of the paper by *** March 1, 2015 ***. The 
formatting guidelines and submission instructions for full papers can be 
found at http://www.umuai.org/paper_submission.html. Papers should not 
exceed 40 pages in journal format.  Each paper submission should note 
that it is intended for the Special Issue on Personality in Personalized 
Systems and be submitted via email to the address mentioned in the 
submission instructions given above (submission at umuai.org).

The tentative timeline for the special issue is as follows:
* December 1, 2014:        Submission of extended abstracts
* December 15, 2014:    Notification regarding abstracts
* March 1, 2015:        Submission of full papers
* June 30, 2015:        First round review notifications
* September 15, 2015:    Revised papers due
* November 15, 2015:    Final notifications due
* December 15, 2015:    Camera-ready papers due
* February 15, 2016:    Publication of special issue



-- 
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Dr. Marko Tkalcic
mailto:marko.tkalcic at gmail.com
http://markotkalcic.wordpress.com
Skype : markotkalcic
Twitter: https://twitter.com/#!/RecSysMare
Linkedin: http://www.linkedin.com/in/markotkalcic
Google Scholar: http://scholar.google.com/citations?user=JQ2puysAAAAJ
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