Effective Use of Machine Learning for Analyzing Sentiments of Social Media Users

The impact of stress and depression on society is significant due to their widespread recognition and handicapping nature. To enhance detection of depression and stress through social networks, automatic monitoring of health play a vital role. The identification of feelings can be achieved through sentiment analysis, which involves use of processing natural language along with content mining approaches. The creation and investigation of systems and devices that have the capability to sense, comprehend, process, and imitate human effects is what computing is all about. Using sentiment analysis and deep learning, it is possible to create powerful technique and frameworks for appraisement and observation of mental issues. This paper focuses on analyzing sentiment through deep learning approach for detecting and monitor depression and stress. A multimodal model for identifying stress and depression is included in fundamental plan, which combines investigation and processing of full- feeling has been proposed in this research work.