Comparative study: different techniques to detect depression using social media
Internet of Things—Applications and Future: Proceedings of ITAF 2019, 2020•Springer
Social media is one of the most influential means of communication in the present day.
Youths and young adults use these sites to communicate with their peers, share information,
reinvent their personalities, and showcase their social lives. Nowadays, not only teenagers
but tens of millions of individuals use internet for the most part of their daily activities and
share information, files, pictures, and video, as well as creating blogs to communicate their
thoughts, personal experiences, and social ideals [1]. Therefore, the potential of social …
Youths and young adults use these sites to communicate with their peers, share information,
reinvent their personalities, and showcase their social lives. Nowadays, not only teenagers
but tens of millions of individuals use internet for the most part of their daily activities and
share information, files, pictures, and video, as well as creating blogs to communicate their
thoughts, personal experiences, and social ideals [1]. Therefore, the potential of social …
Abstract
Social media is one of the most influential means of communication in the present day. Youths and young adults use these sites to communicate with their peers, share information, reinvent their personalities, and showcase their social lives. Nowadays, not only teenagers but tens of millions of individuals use internet for the most part of their daily activities and share information, files, pictures, and video, as well as creating blogs to communicate their thoughts, personal experiences, and social ideals [1]. Therefore, the potential of social media of predicting and detecting, even the prior onset of major depressive disorder in online personas, is very high. In this paper, we discuss how the employment of different machine learning methods and techniques helps in detecting depression on social media [2].
Springer
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