发现青少年眼中的网络毒言常被成人忽略，提出新数据集与检测方法。
"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth
- 构建首个中文青少年毒言数据集，聚焦成人视为无害但对青少年有害的语言。
- 青少年毒言识别受发言者身份和文本特征影响，结合上下文可提升检测准确率。
- 研究为面向青少年的网络内容安全提供新视角，适合教育科技与社会计算研究者。
风险感知具有主观性，青少年对有毒内容的理解与成人存在差异。尽管已有大量关于社交媒体毒性检测的研究，但针对青少年特有的毒性语言——即成人认为无害、对青少年却有害的语言——尚未受到关注。为此，本文以中国青少年为研究对象，构建了首个中文“青少年毒言”数据集，并开展深入分析。结果表明，青少年对这类语言的感知与发言者身份、文本特征等上下文因素密切相关。将这些元信息融入现有检测方法，显著提升了整体识别准确率。最后，本文提出未来以青少年为中心的毒性检测研究方向的若干见解。
原文摘要 · Abstract (English)
Risk perception is subjective, and youth's understanding of toxic content differs from that of adults. Although previous research has conducted extensive studies on toxicity detection in social media, the investigation of youth's unique toxicity, i.e., languages perceived as nontoxic by adults but toxic as youth, is ignored. To address this gap, we aim to explore: 1) What are the features of ``youth-toxicity'' languages in social media (RQ1); 2) Can existing toxicity detection techniques accurately detect these languages (RQ2). For these questions, we took Chinese youth as the research target, constructed the first Chinese ``youth-toxicity'' dataset, and then conducted extensive analysis. Our results suggest that youth's perception of these is associated with several contextual factors, like the source of an utterance and text-related features. Incorporating these meta information into current toxicity detection methods significantly improves accuracy overall. Finally, we propose several insights into future research on youth-centered toxicity detection.
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