通过计算机化语言分析,自动检测语言跨群偏差
Katherine A Collins1, Ryan L Boyd2
1University of Saskatchewan, Saskatoon, SK, Canada.
Journal of language and social psychology
|April 28, 2025
概括
这项研究引入了一种自动化方法来检测语言偏见,特别是语言跨组偏见 (LIB). 使用情感分析和抽象的自动编码为手动分析提供了一个有希望的替代方案.
科学领域:
- 心理语言学 心理语言学
- 计算语言学 计算语言学
- 社会心理学 社会心理学
背景情况:
- 语言偏见涉及对跨群体行为进行差异抽象.
- 语言类型模型 (LCM) 定义了一个具体到抽象的词连续.
- 语言跨群偏见 (LIB) 反映在抽象/具体的词汇使用中,用于内组/外组行为.
研究的目的:
- 开发一种编码语言跨组偏差 (LIB) 的自动化方法.
- 为了克服LIB研究中耗时的手动编码的局限性.
主要方法:
- 使用句子标记化,情感分析和抽象编码.
- 采用自动化方法,包括CoreNLP情绪分析和LCM词典抽象编码.
主要成果:
- 自动编码方法产生了接近手工编码的得分.
- 这表明LIB编码可能不需要复杂的方法.
结论:
- 自动化方法对于编码语言间群偏差 (LIB) 是有效的.
- 建议使用CoreNLP情绪分析和LCM词典抽象编码来检测LIB.
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