The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos
The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos
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DOI：
10.1145/2659522.2659529
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
S. Gievska;Kiril Koroveshovski
中科院分区：
文献类型：
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作者：
S. Gievska;Kiril Koroveshovski
人性始终意味着预测建模面临着巨大的挑战，而这些挑战尚未得到充分探索。在本文中，我们报告了一项实验，该实验检查了视频记录中的性别和情感内容对预测被评判者的个性印象的预测效果。虽然性别对所有人格特征的可预测性都有积极影响，但情感特征的影响因特征而异。粗粒度的情感类别导致宜人性和神经质的表现提高，而细粒度的情感特征的包含对预测外向性和体验开放性有更积极的影响。初步结果令人鼓舞，并且与相关研究具有可比性。
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.