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.

翻译：社交媒体平台改变了传统的沟通方式,使世界各地的用户能够即时、公开和经常地进行沟通。人们利用社交媒体表达他们的意见,分享他们的个人故事和斗争。社交媒体中,特别是年轻一代中,普遍存在表达困难、死亡想法和自我伤害的消极情绪。因此,利用社交媒体探测和识别自杀思想将有助于提供适当的干预,最终劝阻他人避免自残和自杀,并防止自杀思想在社交媒体上传播。许多研究已经开展,目的是查明社交媒体中的自杀思想和行为。本文件全面概述了目前利用社交媒体机器学习算法检测自杀思想的研究努力。本审查24项研究调查社交媒体使用自杀思想发现的可行性,目的是促进该领域的进一步研究,并将成为从事自杀文字分类的研究人员的有益资源。