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WCPR '14: Proceedings of the 2014 ACM Multi Media on Workshop on Computational Personality Recognition
ACM2014 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
MM '14: 2014 ACM Multimedia Conference Orlando Florida USA 7 November 2014
ISBN:
978-1-4503-3129-6
Published:
07 November 2014
Sponsors:
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Abstract

It is our great pleasure to welcome you to the 2014 ACM Multi Media - Workshop on Computational Personality Recognition (WCPR'14). This is the second edition of the WCPR and we are really glad to be hosted in a great conference like ACMMM. After a first successful edition, this year's symposium continues its tradition of allowing participants to run experiments on personality recognition on the same benchmarks. We believe that the research results, including models, systems, applications, and theoretical findings, together with the experience reports on leading edge issues in the emerging field of personality recognition, will be extremely significant for future research. In particular, the mission of the WCPR is to share data and tools, that will make easier the comparison of the results for future systems and applications in personality recognition. The WCPR'14 gives researchers and practitioners a unique opportunity to compete with their systems or prototypes for personality recognition from text and multimedia signals.

The call for papers attracted many submissions, in particular from Europe and United States. The program committee accepted 6 papers that cover a variety of topics, including feature selection, application of new and old resources, and evaluation of algorithms for the automatic prediction of personality types.

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SESSION: Competition
research-article
A Multivariate Regression Approach to Personality Impression Recognition of Vloggers

Research in psychology has suggested that behavior of individuals can be explained to a great extent by their underlying personality traits. In this paper, we focus on predicting how the personality of YouTube video bloggers is perceived by their ...

research-article
Evaluating Content-Independent Features for Personality Recognition

This paper describes our submission for the WCPR14 shared task on computational personality recognition. We have investigated whether the features proposed by Soler and Wanner (2014) for gender prediction might also be useful in personality recognition. ...

research-article
Feature Analysis for Computational Personality Recognition Using YouTube Personality Data set

It is an important yet challenging task to develop an intelligent system in a way that it automatically classifies human personality traits. Automatic classification of human traits requires the knowledge of significant attributes and features that ...

research-article
Predicting Personality Traits using Multimodal Information

Measuring personality traits has a long story in psychology where analysis has been done by asking sets of questions. These question sets (inventories) have been designed by investigating lexical terms that we use in our daily communications or by ...

SESSION: Shared Task
research-article
The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos

Human nature as always implies massive challenges for predictive modeling that are yet to be fully explored. In this paper, we report on an experiment that examines the predictive effect of the gender and the affective content of video transcripts on ...

research-article
Look! Who's Talking?: Projection of Extraversion Across Different Social Contexts

Automatic classification of personality from language depends upon large quantities of relevant training data, which raises two potential problems. First, collecting personality information from the author or speaker can be invasive and expensive, ...

Contributors
  • University of Trento
  • Bruno Kessler Foundation

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  1. Proceedings of the 2014 ACM Multi Media on Workshop on Computational Personality Recognition
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          Acceptance Rates

          WCPR '14 Paper Acceptance Rate 6 of 11 submissions, 55%;
          Overall Acceptance Rate 6 of 11 submissions, 55%
          YearSubmittedAcceptedRate
          WCPR '1411655%
          Overall11655%