通过词嵌入来检测阿拉伯文文本中的性别偏见
Aya Mourad1, Fatima K Abu Salem1, Shady Elbassuoni1
1Computer Science Department, American University of Beirut, Beirut, Lebanon.
PloS one
|March 31, 2025
概括
这项研究揭示了阿拉伯文中持续存在的性别刻板印象,将男性与职业,女性与家庭/艺术联系在一起. 对新闻档案和在线文本的分析显示,职业代表性存在偏见,这凸显了阿拉伯世界需要进一步研究的需要.
科学领域:
- 计算语言学 计算语言学
- 社会语言学 社会语言学
- 性别研究是性别研究.
背景情况:
- 历史上对西方妇女权利和经济地位的关注使得其他地区,比如中东,没有得到充分的研究.
- 阿拉伯世界缺乏基于性别的经济统计数据,因此需要采用替代方法来评估性别差异.
- 社会认知理论认为,语言反映了社会规范,这使得文本分析对于理解性别偏见至关重要.
研究的目的:
- 检查阿拉伯文字体内的职业代表性中的基于性别的偏见.
- 适应和应用词嵌入协会测试 (WEAT) 和直接偏差量化测试的阿拉伯语.
- 提供阿拉伯世界持续存在的性别刻板印象的证据,特别是在没有全面的人口普查数据的情况下.
主要方法:
- 适应WEAT和直接偏差量化测试的阿拉伯语言.
- 分析各种阿拉伯文本数据集,包括黎巴嫩新闻档案,阿拉伯维基百科和阿联,埃及和摩洛哥的电子报纸.
- 使用词嵌入模型来检测和量化职业方面与性别相关的偏见.
主要成果:
- WEAT测试始终将职业,科学和智力追求的术语与所有数据集中的男性联系在一起.
- 在分析的文本中,与家庭和艺术相关的术语主要与女性有关.
- 直接偏见分析揭示了一种一致的偏见,将女性与护士,清洁工,女仆和秘书等角色联系起来,一些数据集还将她们与研究人员,医生和教授联系起来.
结论:
- 阿拉伯语文本数据集反映了有关职业的重大性别刻板印象.
- 这些发现提供了在阿拉伯世界持续存在的性别偏见的经验证据,尽管统计数据有限.
- 这项研究强调了批判性话语分析对于理解和解决语言中反映的性别不平等的重要性.
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