CapsF:从Twitter中提取自杀精神压力源的胶囊融合

Mohammad Ali Dadgostarnia , Ramin Mousa , Saba Hesaraki , Mahdi Hemmasian
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引用次数: 0

摘要

与癌症、血压、街头交通事故和中风等因素一起,自杀一直是伊朗人死亡的主要原因之一。自杀的主要原因之一是心理压力。识别高危人群的心理压力源有助于早期预防自杀和自杀行为。近年来,社交媒体的广泛普及和实时信息共享的流动,为大规模甚至小规模人群的早期干预提供了可能。然而,已经提出了一些从Twitter中提取精神压力源的自动化方法,但大多数研究都是非波斯语的。本研究旨在探讨使用基于学习的方法从波斯语推特中检测与自杀相关的精神压力的技术。该方法的二值分类准确率为0.83。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CapsF: Capsule Fusion for Extracting psychiatric stressors for suicide from Twitter
Along with factors such as cancer, blood pressure, street accidents and stroke, suicide has been one of Iran’s main causes of death. One of the main reasons for suicide is psychological stressors. Identifying psychological stressors in an at-risk population can help in the early prevention of suicidal and suicidal behaviours. In recent years, the widespread popularity and flow of real-time information sharing of social media have allowed for potential early intervention in large-scale and even small-scale populations. However, some automated approaches to extract psychiatric stressors from Twitter have been presented, but most of this research has been for non-Persian languages. This study aims to investigate the techniques of detecting psychiatric stress related to suicide from Persian tweets using learning-based methods. The proposed capsule-based approach achieved a binary classification accuracy of 0.83.
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