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预测YouTube用户的MBTI人格
Luisa Stracqualursi1, Patrizia Agati2
1Department of Statistics, University of Bologna, Bologna, 40126, Italy. luisa.stracqualursi@unibo.it.
Scientific reports
|February 28, 2025
概括
这项研究使用机器学习和自然语言处理来从社交媒体文本中预测人格类型. 内向和直观的人,特别是INFP和INTP类型,在在线讨论中最常见.
科学领域:
- 计算社会科学 计算社会科学
- 心理学信息学 心理学信息学
- 自然语言处理自然语言处理.
背景情况:
- 人格评估传统上依赖于自我报告问卷.
- 新兴的计算方法为人格分析提供了替代方法.
研究的目的:
- 开发和应用机器学习分类器来预测迈尔斯-布里格斯类型指标 (MBTI) 人格类型.
- 分析评论特定内容类型的YouTube用户的个性类型.
主要方法:
- 利用自然语言处理 (NLP) 和机器学习 (ML) 来构建个性分类器.
- 从YouTube评论中提取文本样本进行分析.
- 根据评论内容将用户分为MBTI类型.
主要成果:
- 准确的个性类型估计可以通过每位用户大约100个与主题相关的单词来实现.
- 在分析的YouTube用户中,INFP成为最常见的MBTI类型.
- INTP是阴谋论评论的主要类型,而INFP则主导了精神和旅行内容讨论.
结论:
- 对社交媒体文本的计算分析提供了一种可行的方法来评估人格类型.
- 内向和直观 (N) 个性特征在在线评论中得到了显著的代表.
- 内容主题影响在线用户参与中观察到的人格类型的分布.
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