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一种以表情符号为中心的方法来检测在线话语中的刺言论

V Grover¹, H Banati²

¹Department of Computer Science, University of Delhi, New Delhi, India.

Scientific reports

|January 28, 2026

概括

这项研究引入了一种以表情符号为中心的刺言论检测方法,揭示了表情符号.

科学领域:

自然语言处理自然语言处理.
计算语言学计算语言学
情绪分析情绪分析

背景情况:

刺言论的检测对于分析在线沟通至关重要,特别是在社交媒体平台上.
表情符号是多种类型的,经常与刺言论检测的其他模式一起使用.
现有的方法经常忽略了表情符号在识别刺的独立贡献.

研究的目的:

调查表情符号在刺言论检测中的特定作用.
提出和评估一种以表情符号为中心的方法来对刺言论进行分类.
开发新的表情符号嵌入,以改进刺言论的检测.

主要方法:

一种结构化的方法,分析表情符号的特征,情绪,频率和位置.
实验各种机器学习分类器.
微调的BERT (变压器的双向编码器表示) 模型与特定的表情符号数据.
开发新的刺意识的基于GloVe的表情符号嵌入.

主要成果:

即使没有其他上下文信息,表情符号在刺言论的检测中起着决定性的作用.
提出的以表情符号为重点的模型和嵌入式显著优于现有方法.
新型表情符号嵌入在未见的数据集上获得了最高的F1,MCC和RoC_AuC分数.

结论:

表情符号是刺的强有力的指标,并且可以独立有效地使用.
开发的表情符号嵌入和模型为未来的刺言论检测研究提供了强有力的基础.
这种以表情符号为中心的方法可以帮助识别数字平台上的网络欺凌和仇恨言论等有害内容.

关键词:

在刺言论检测中的表情符号多种类型的表情符号刺言论检测检测刺言论检测情绪分析是一种情绪分析.

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