A System for Personality and Happiness Detection

Y. Sáez, Carlos Navarro, A. Mochón, P. I. Viñuela
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引用次数: 11

Abstract

This work proposes a platform for estimating personality and happiness. Starting from Eysenck's theory about human's personality, authors seek to provide a platform for collecting text messages from social media (Whatsapp), and classifying them into different personality categories. Although there is not a clear link between personality features and happiness, some correlations between them could be found in the future. In this work, we describe the platform developed, and as a proof of concept, we have used different sources of messages to see if common machine learning algorithms can be used for classifying different personality features and happiness.
一个人格和幸福检测系统
这项工作提出了一个评估人格和幸福的平台。从艾森克的人格理论出发,作者试图提供一个收集社交媒体(Whatsapp)短信的平台,并将其分类为不同的人格类别。虽然性格特征和幸福之间没有明确的联系,但将来会发现它们之间的一些相关性。在这项工作中,我们描述了开发的平台,作为概念的证明,我们使用了不同的消息来源,看看常见的机器学习算法是否可以用于分类不同的个性特征和幸福。
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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