论文标题
社交媒体上的自杀念头检测：机器学习方法的审查
Suicidal Ideation Detection on Social Media: A Review of Machine Learning Methods
论文作者
论文摘要
社交媒体平台通过允许用户在全球范围内，公开，公开和频繁的沟通来改变传统的通信方法。人们使用社交媒体表达自己的意见并分享他们的个人故事和挣扎。在社交媒体中，尤其是在年轻一代中，表达艰辛，死亡和自我伤害的负面情绪在社交媒体中普遍存在。因此，使用社交媒体来检测和确定自杀的念头将有助于提供适当的干预措施，最终将阻止他人自杀和自杀，并防止自杀念头在社交媒体上传播。已经进行了许多研究，以确定社交媒体中的自杀念头和行为。本文介绍了当前研究工作的全面摘要，该研究旨在使用社交媒体上的机器学习算法来检测自杀意念。这篇评论24研究了社交媒体使用对自杀意念检测的可行性的研究旨在促进该领域的进一步研究，并将成为从事自杀文本分类的研究人员的有益资源。
Social media platforms have transformed traditional communication methods by allowing users worldwide to communicate instantly, openly, and frequently. People use social media to express their opinion and share their personal stories and struggles. Negative feelings that express hardship, thoughts of death, and self-harm are widespread in social media, especially among young generations. Therefore, using social media to detect and identify suicidal ideation will help provide proper intervention that will eventually dissuade others from self-harming and committing suicide and prevent the spread of suicidal ideations on social media. Many studies have been carried out to identify suicidal ideation and behaviors in social media. This paper presents a comprehensive summary of current research efforts to detect suicidal ideation using machine learning algorithms on social media. This review 24 studies investigating the feasibility of social media usage for suicidal ideation detection is intended to facilitate further research in the field and will be a beneficial resource for researchers engaged in suicidal text classification.
