A Scoping Review of Depression Detection Using Machine Learning and Deep Learning Techniques on Social Networks

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M. Yohapriyaa, Dr. M. Uma


Depression or major depressive disorder is one of the serious health issues in this currentera. According to World Health Organization (WHO) depression disorders will become predominant disease in next successive 20 years. Depression is a major cause for suicidal thoughts hence it is significant to detect and prevent depression at initial stage. Social media sites created a platform for many peoples to express their emotions and feelings in day-to-day activity. The emotional state of a user can be predicted by analysing the content expressed by them in social media. The main aim of this survey is to establish the previous research work done in the field of detecting depression using machine learning and deep learning based on thedata shared by them on social media networks. Thetraditional method is based on various questionnaire technique to detectdepression but it is costly and not accurate. Recently many researches focus on detecting depression based on the content expressed by them in social network sites. This paper focus on various techniques and algorithms implemented in the area of detecting depression.

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