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CHI-ANNOUNCEMENTS  November 2014, Week 4

CHI-ANNOUNCEMENTS November 2014, Week 4

Subject:

Final CFP: UMUAI Special Issue on Personality in Personalized Systems

From:

Sabine Graf <[log in to unmask]>

Reply-To:

[log in to unmask]

Date:

Thu, 27 Nov 2014 00:12:15 -0700

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (161 lines)

********************************************************************
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/
*********************************************************************


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 ([log in to unmask]).

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


GUEST EDITORS:

Marko Tkalčič, Johannes Kepler University, Linz, Austria
[log in to unmask]

Daniele Quercia, Yahoo Labs, Barcelona, Spain [log in to unmask]

Sabine Graf, Athabasca University, Edmonton, Canada [log in to unmask]

    ---------------------------------------------------------------
    For news of CHI books, courses & software, join CHI-RESOURCES
     mailto: [log in to unmask]

    To unsubscribe from CHI-ANNOUNCEMENTS send an email to
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April 2004, Week 1
March 2004, Week 1
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April 2001, Week 4
April 2001, Week 3
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March 2001, Week 5
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March 2001, Week 1
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December 1998, Week 4
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December 1997, Week 3
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