论文标题
我不好吗？旨在发现自杀记录中的繁琐和挫败的归属感
Am I No Good? Towards Detecting Perceived Burdensomeness and Thwarted Belongingness from Suicide Notes
论文作者
论文摘要
世界卫生组织（WHO）强调了明显加速自杀预防的重要性，以实现2030年联合国可持续发展目标（SDG）目标。在本文中，我们提出了一个端到端的多任务系统，以解决两种自我室内风险因素的新任务，以自我感知到的伯氏burdensementes（pb）（pb）（pb）（pb）（pb）。我们还基于基准cease-cease-v2.0数据集，介绍了一个手动翻译的代码混合说明语料库，即comcease-v2.0，并用时间方向注释，PB和TB标签。我们利用自杀记录中的时间定向和情感信息来提高整体表现。为了全面评估我们提出的方法，我们将其与现有的CEASE-V2.0数据集和新公布的Comcease-V2.0数据集的几种最新方法进行了比较。经验评估表明，时间和情感信息可以大大改善PB和TB的检测。
The World Health Organization (WHO) has emphasized the importance of significantly accelerating suicide prevention efforts to fulfill the United Nations' Sustainable Development Goal (SDG) objective of 2030. In this paper, we present an end-to-end multitask system to address a novel task of detection of two interpersonal risk factors of suicide, Perceived Burdensomeness (PB) and Thwarted Belongingness (TB) from suicide notes. We also introduce a manually translated code-mixed suicide notes corpus, CoMCEASE-v2.0, based on the benchmark CEASE-v2.0 dataset, annotated with temporal orientation, PB and TB labels. We exploit the temporal orientation and emotion information in the suicide notes to boost overall performance. For comprehensive evaluation of our proposed method, we compare it to several state-of-the-art approaches on the existing CEASE-v2.0 dataset and the newly announced CoMCEASE-v2.0 dataset. Empirical evaluation suggests that temporal and emotional information can substantially improve the detection of PB and TB.
