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In these past few years, there has been a huge growth in the use of microblogging and social media updating. Prodded by that development, organizations are looking for approaches to mine data about the thing individuals are feeling. Our undertaking is to fabricate a compelling framework to mine the estimations/psychological wellness of individuals during Coronavirus pandemic. Our project is to build an effective system to mine the sentiments/ mental health of people during COVID-19 pandemic. It is to effectively analyze, extract, and train a vast amount of data. The results will classify the customer's perspective into negative and positive sentiments. To help us classify the texts in an easier way, hashtags will be an added advantage. By collecting valuable information, we apply the machine learning algorithm BERT to train our model to recognize the sentiments to provide the best accuracy. confidentiality. Main objective is to help a user understand his/ her mental state as much as possible and to self-regulate. To provide end-to-end encryption of user bot interaction since it is sensitive information.