文化相似性提升波斯语有害语言检测的跨语言迁移效果
Culture Matters in Toxic Language Detection in Persian
- 对比多种方法在波斯语有害内容检测中的表现
- 文化相近语言的迁移学习效果优于文化差异大的语言
- 研究结果对跨文化社交媒体治理有参考价值
有害语言检测对于营造更安全的网络环境至关重要。尽管波斯语领域的相关研究较少，本文对比了微调、数据增强、零样本与少样本学习以及跨语言迁移学习等多种方法。特别发现：文化背景与波斯语相近国家的语言在迁移学习中表现更优；而文化差异较大的语言则提升效果有限。文中包含有害语言示例，仅用于研究目的，可能引起不适。
原文摘要 · Abstract (English)
Toxic language detection is crucial for creating safer online environments and limiting the spread of harmful content. While toxic language detection has been under-explored in Persian, the current work compares different methods for this task, including fine-tuning, data enrichment, zero-shot and few-shot learning, and cross-lingual transfer learning. What is especially compelling is the impact of cultural context on transfer learning for this task: We show that the language of a country with cultural similarities to Persian yields better results in transfer learning. Conversely, the improvement is lower when the language comes from a culturally distinct country. Warning: This paper contains examples of toxic language that may disturb some readers. These examples are included for the purpose of research on toxic detection.
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