The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos

WCPR '14 Pub Date : 2014-11-07 DOI:10.1145/2659522.2659529
S. Gievska, Kiril Koroveshovski
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引用次数: 15

Abstract

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 predicting personality impressions of the person being judged. While gender had positive impact on the predictability across all personality traits, the effects of the emotional features varied across traits. Coarse-grain emotional categories resulted in performance gains for Agreeableness and Neuroticism, while the inclusion of fine-grain emotional features had more positive effect on predicting Extroversion and Openness to Experiences. The initial results are encouraging and comparable to related research.
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情感性言语内容对预测YouTube视频中人格印象的影响
人类的本性总是意味着对预测建模的巨大挑战,这些挑战尚未得到充分的探索。在本文中,我们报告了一项实验,该实验检验了性别和视频文本的情感内容对预测被评判人人格印象的预测作用。虽然性别对所有人格特征的可预测性都有积极影响,但情绪特征的影响在不同性格特征之间存在差异。粗粒度的情绪特征对亲和性和神经质的预测有显著影响,而细粒度的情绪特征对外向性和开放性的预测有更积极的影响。初步结果令人鼓舞,并可与相关研究相媲美。
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Predicting Personality Traits using Multimodal Information Evaluating Content-Independent Features for Personality Recognition Look! Who's Talking?: Projection of Extraversion Across Different Social Contexts The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos A Multivariate Regression Approach to Personality Impression Recognition of Vloggers
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