• Dr. Pharindra Sharma
• Dambarbhadur Rawal

In the current days maximum people like teenagers, adult are using social media network. One of the biggest differences in the lives of current teenagers and young adults, as compared to earlier generations, is that they spend much time on social media network to connecting directly with peoples and more time connecting electronically, principally through social media. Some experts see the rise in depression or some mental illness as evidence because social media users are sitting on online more than hours. Twitter, Facebook becomes the most popular social media platform that allows people to share the information through small messages called tweets on a real time basis. The proposed method uses concepts like Natural Language Processing for text analysis. This system will analyze the sentiments as positive or negative using Text blob’s sentiment method based on that the system will detects the different levels of depression and to find mental illness using machine learning.

Machine Learning, Classification Model, Social network, Emotions

"Mental illness/Depression Detection from social media data using machine learning techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.a383-a389, February-2022, Available :http://www.jetir.org/papers/JETIR2202049.pdf

"Mental illness/Depression Detection from social media data using machine learning techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppa383-a389, February-2022, Available at : http://www.jetir.org/papers/JETIR2202049.pdf