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Analyzing human behaviors using computer-based approaches is a new dimension of digital humanity. It integrates computing with healthcare, psychology, and social media. Like other healthcare and medical-related problems, anxiety and depressive disorders are common in Pakistan. In the existing era, this disease is not only affecting people of all ages but the impact of depression is also witnessed on social media communications. On social media, anyone could not guess about the mental conditions of a user through his/ her tweets or comments. Especially, the prediction of depressed unknown users through his behavior on social media is a hard task. Computer science and the medical domain can eliminate such healthcare-related issues. In this paper, a system has been proposed to detect and analyze the behavior of a user on social media. The proposed system comprises of an algorithm that performs sentimental analysis of users’ tweets and comments and a web-based platform to share best practices and success stories of users who have recovered from the disease. The system has been tested on real-time data obtained from tweeter using Application Programming Interface (API). Top trends have been focused to obtain the data and the proposed system successfully detected the users under depression. After working on the huge dataset, the proposed system will be a good contribution to humanity. [ABSTRACT FROM AUTHOR]