关于认知扭曲的数据集,用于印尼语文的文本分类
Nyoman Putra Sastra1, Linawati1, Gede Sukadarmika1
1Department of Doctoral Engineering, Faculty of Engineering, University of Udayana, Denpasar 80113, Indonesia.
Data in brief
|July 21, 2025
概括
这项研究引入了第一个用于检测认知扭曲的印度尼西亚数据集,这是抑郁症的关键因素. 这个NLP资源有助于心理健康研究和低资源语言的工具开发.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算心理学 计算心理学
- 心理健康研究 心理健康研究
背景情况:
- 认知扭曲是信息处理中的系统偏见,加强了消极思维并导致了抑郁症.
- 开发用于识别认知扭曲的工具对于心理健康支持至关重要.
- 印尼语中缺乏对认知扭曲的注释数据集,这是一个资源较低的语言.
研究的目的:
- 创建并呈现一种新的印尼语数据集,对认知扭曲进行注释.
- 为了促进NLP在文本分类中的研究,用于心理健康应用.
- 支持印尼的计算心理学研究和心理健康倡议.
主要方法:
- 数据收集涉及印尼参与者 (18岁以上) 的问卷,包括人口统计信息,心理健康史和与生活有关的开放式问题.
- 两个执照的心理学家手动注释句子,识别和分类认知扭曲成10种类型.
- 使用逆向翻译进行数据增强以解决类不平衡,最终数据集大小为4992条条目.
主要成果:
- 该数据集包含4,992个印尼语句子,标记为认知扭曲的存在和类型.
- 它包括2,246个非扭曲和2,416个扭曲的实例,进一步增强产生4,992条条目.
- 这是印尼首个专门针对心理健康领域认知扭曲的文本分类数据集.
结论:
- 开发的数据集是NLP研究的宝贵资源,特别是在心理健康的文本分类中.
- 它为创建NLP工具提供了基础,以检测低资源语言中的认知扭曲.
- 这项工作为印尼的心理健康研究和计算语言学做出了重大贡献.
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