Early Detection of Depression Indication from Social Media Analysis

ITM Web of Conferences

Syed Maharukh¹  Narvekar Meera² 

[1] D.J .Sanghvi College of Engineering;Department of Computer Engineering, D.J.Sanghvi College of Engineering;

关键词: social media analysis;    natural language processing;    embedding system;    tag cloud;    cnn;   

DOI  :  10.1051/itmconf/20214003029

来源: DOAJ

【 摘 要 】

Depression that stems through social media has been steadily growing since the past few years but with the current inclination towards social media reliance it is highly imperative to detect the early signs. Continuous observation of a user's social media interests and activities may highlight suspicious and negative thoughts. This observation can help in understanding their future course of action and also indicate any suicidal thoughts and behaviors. By using the machine learning models, early indications of depression detection can be addressed. This work studies different word embedding techniques for early detection of depression from social media posts. Further, this work develops a model using various NLP processes in order to address the issue of early detection. The recommendations can be useful as a Decision Support System for counselors, psychologist and also can be of good use by the cyber-crime cell department for criminal investigations.

【 授权许可】

Unknown