Coronavirus Disease 2019 (COVID-19) has become a significant worldwide issue with a rising the number of infected people and increases in mortality. Among every single helpful methodologies, contentions have raised about hydroxychloroquine (HCQ) viability in the treatment of COVID-19. The utilization of hydoxychloroquine is acknowledged as commonly accepted for patients with malaria and autoimmune diseases, however its utilization where not demonstrated and without clinical management can cause genuine results and ought to be maintained a strategic distance. This research carried out a sentiment analysis regarding the effectiveness of hydroxychloroquine in the treatment of COVID-19.

Sentimental Analysis is the way toward recognizing concept from text written based on Natural Language Processing the element it is alluding to. Twitter is an informal community that allows clients to post their suppositions about current issues, share their get-togethers, and associate with others. Twitter has now gotten probably the biggest wellspring of information, with more than 200 million dynamic clients month to month. The technique concentrates and investigations sentimental data from microblogs to forecast the patient’s assessment of hydroxychloroquine. In this work, a pre-handling strategy for assessment mining is executed and will be used for examining patients’ remarks on Twitte’ social media about hydroxychloroquine. The different content pre-handling strategies have been used on the dataset to accomplish a sufficient standard text.