New research uncovers how social network information can be utilized to predict users’ psychological and physical wellbeing, adding to a developing number of researchers utilizing social media to make startlingly precise forecasts from the most basic data. The same number of users think what they share on the web, the discoveries give occasion to feel qualms about customary thoughts of "safe" surfing. In spite of the fact that rates of diagnosing mental illness have enhanced in the course of recent decades, numerous cases stay undetected. Side effects related with mental illness are noticeable on Twitter, Facebook, and web forums, and automated techniques are progressively ready to identify misery and other psychological instabilities. In this paper, late investigations that expected to anticipate psychological sickness utilizing web-based social networking are explored. . Mentally ill users have been observed utilizing screening reviews, their open sharing of a determination on Twitter, or by their participation in an online discussion, and they were discernable from control users by designs in their language and online activity. Automated detection techniques may recognize discouraged or generally in danger people through the vast scale passive monitoring of social media, and in the future may complement existing screening methodology.

Social Media, Prediction, Classification, Image, Probabilities, Decisiontree

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