Personality Analysis Using Classification on Turkish Tweets

Pub Date : 2021-10-01 DOI:10.4018/ijcini.287596
G. Mavis, I. H. Toroslu, P. Senkul
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引用次数: 4

Abstract

According to the psychology literature, there is a strong correlation between the personality traits and the linguistic behavior of people. Due to increase in computer based communication, individuals express their personalities in written forms on social media. Hence, social media became a convenient resource to analyze the relationship between the personality traits and the lingusitic behaviour. Although there is a vast amount of studies on social media, only a small number of them focus on personality prediction. In this work, we aim to model the relationship between the social media messages of individuals and Big Five Personality Traits as a supervised learning problem. We use Twitter posts and user statistics for analysis. We investigated various approaches for user profile representation, explored several supervised learning techniques, and presented comparative analysis results. Our results confirm the findings of psychology literature, and we show that computational analysis of tweets using supervised learning methods can be used to determine the personality of individuals.
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基于分类的土耳其语推文个性分析
根据心理学文献,人们的性格特征和语言行为之间有很强的相关性。由于计算机通信的增加,个人在社交媒体上以书面形式表达他们的个性。因此,社交媒体成为分析人格特质与语言行为关系的便利资源。虽然有大量关于社交媒体的研究,但只有少数研究关注人格预测。在这项工作中,我们的目标是将个人的社交媒体信息与大五人格特质之间的关系建模为一个监督学习问题。我们使用Twitter帖子和用户统计数据进行分析。我们研究了用户概要表示的各种方法,探索了几种监督学习技术,并给出了比较分析结果。我们的研究结果证实了心理学文献的发现,我们表明,使用监督学习方法对推文进行计算分析可以用来确定个体的性格。
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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