论文标题
在社交媒体中理解和检测危险的言论
Understanding and Detecting Dangerous Speech in Social Media
论文作者
论文摘要
社交媒体沟通已成为现代社会日常活动的重要组成部分。因此，必须确保社交媒体平台的安全是必要的。在在线环境中使用诸如身体威胁之类的危险语言在某种程度上很少见，但仍然非常重要。尽管已经在检测令人讨厌和仇恨语言的相关问题上进行了几项著作，但以前尚未以任何重要的方式对待危险的言论。在这些观察结果的推动下，我们报告了为构建标有危险言论的标签数据集的努力。我们还利用数据集开发高效模型来检测危险内容。我们的最佳模型在59.60％的宏F1上的表现明显优于竞争性基线。
Social media communication has become a significant part of daily activity in modern societies. For this reason, ensuring safety in social media platforms is a necessity. Use of dangerous language such as physical threats in online environments is a somewhat rare, yet remains highly important. Although several works have been performed on the related issue of detecting offensive and hateful language, dangerous speech has not previously been treated in any significant way. Motivated by these observations, we report our efforts to build a labeled dataset for dangerous speech. We also exploit our dataset to develop highly effective models to detect dangerous content. Our best model performs at 59.60% macro F1, significantly outperforming a competitive baseline.
