社交网络内容中的抑郁检测模型研究

E. M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref
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摘要

社交媒体(SM)是一个每天产生大量数据的平台,允许个人相互交流。对于很多人来说,社交媒体已经演变成一种生活方式和日常生活的第五个组成部分。最受欢迎的社交媒体平台包括Facebook、Instagram、Twitter、WhatsApp和Snapchat。抑郁症是一种常见且危险的疾病,它会对你的感觉、思考和行为产生负面影响。治疗师快速发现人们抑郁的能力是有限的,因为他们无法观察到一个人一整天的情绪。研究人员可以通过社交媒体来评估一个人的情绪,通过查看用户的帖子和评论来发现他或她是否有精神问题。这项调查研究反映了先前使用社交媒体平台上的用户生成材料来检测抑郁症的研究,这些研究引入了不同的技术,并在它们之间进行了比较,以获得准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Depression Detection Model in Social Network Content: A Survey
Social media (SM) is a platform that generates a massive quantity of data every day and allows individuals to engage with one another. For many people, social media has evolved into a way of life and the fifth component of daily living. Among the most popular social media platforms are Facebook, Instagram, Twitter, WhatsApp, and Snapchat. Depression is a frequent and dangerous medical condition that has a negative impact on how you feel, think, and act. A therapist's ability to swiftly detect depression in persons is limited since they cannot observe a person's mood throughout the day. Researchers can assess a person's sentiments via social media by looking at the user's posts and comments to discover if he or she has a mental issue. This survey study mirrors prior research on detecting depression using user-generated material from social media platforms, which introduce different techniques and compare between it to obtain accuracy.
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