Detecting Individuals High in Neuroticism based on the Color Features of the Facebook Profile Picture

D. Dudău, F. Sava, Andrei A. Rusu, Virgil Cervicescu
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引用次数: 1

Abstract

Previous research has mostly focused on the link between the linguistic and behavioral footprints found on social media on the one hand and personality on the other. Despite the high amount of image-based contents posted and shared online and the valuable implicit information they might conceal about users' preferences and tendencies, the study of visual traces is in its infancy. The goal of the current paper is to test whether the color characteristics of the Facebook profile picture could mirror the level of neuroticism on a sample of 508 Romanian users. For this purpose, we assessed the classification performance of four machine learning algorithms having as input three sets of visual features: (1) the colorfulness, which indicates how colorful is an image; (2) the proportion of cold colors, along with the mean and standard deviation for saturation and value; (3) the emotional load, defined as pleasure, arousal, and dominance. None of the models showed good accuracy. However, this paper contributes to the literature by being part of a line of research that requires development not only in Romania but also worldwide.
基于Facebook头像颜色特征的高神经质个体检测
之前的研究主要集中在社交媒体上的语言和行为足迹与个性之间的联系上。尽管基于图像的内容在网上发布和分享的数量很大,而且它们可能隐藏了关于用户偏好和倾向的有价值的隐含信息,但视觉痕迹的研究仍处于起步阶段。目前这篇论文的目的是测试Facebook个人资料图片的颜色特征是否能反映508名罗马尼亚用户的神经质程度。为此,我们评估了四种机器学习算法的分类性能,并将其作为三组视觉特征的输入:(1)彩色度,表示图像的彩色程度;(2)冷色的比例,以及饱和度和值的平均值和标准差;(3)情绪负荷,定义为愉悦、兴奋和支配。没有一个模型显示出很好的准确性。然而,本文通过成为不仅在罗马尼亚而且在世界范围内需要发展的一系列研究的一部分,为文献做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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