ajansha/SOCIAL-ANXIETY-DETECTION-USING-NEURAL-NETWORKS

Use of Social Networking Sites (SNS) and prevalence of anxiety and depression among the young population is on the rise. Millions of users share opinions on different aspects of life every day. The online medium has become a significant way for people to express their opinions and with social media, there is an abundance of opinion information available. Using sentiment analysis, the polarity of opinions can be found, such as positive, negative, or neutral by analyzing the text of the opinion. There are many ways in which social network data can be leveraged to give a better understanding of user opinion such problems are at the heart of natural language processing (NLP) and data mining research. Although diagnosis of depression using social networks data has picked an established position globally, there are several dimensions that are yet to be detected. The anxiety identification system is not a single process. This system consists of various modules. The success rate of each and every step is highly important to ensure the high accuracy of the system.

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