Sentiment Analysis of Public on Social Media about Covid-19 origin theory using Machine Learning

Covid-19 has been found in Wuhan, China, for approximately a year and a half ago, and the virus's origin remains a mystery. However, it has been in the news in recent weeks, with reports suggesting that an infectious disease was spilled in a Chinese laboratory, which was previously refuted by a hoax in the area. In this research paper, we have presented a model where there will be a sentimental analysis based on users’ comments on social media about the origin of corona virus. Nowadays most people express their feelings and the truth around them and many lies on social media. And we are taking this opportunity to do a sentimental analysis of the true, false, and confusing feelings that people have expressed on social media about the origin of corona virus. We used 20000 data (comments) taken from corona virus-related popular Facebook news posts. In order to achieve the maximum results, we used five distinct machine learning classifiers, and our support vector machine and logistic regression model outscored them all. The support vector model had a testing accuracy rate of 83.73 %, whereas logistic regression had an accuracy rate of 81.39 %. The important thing about our research is that at the end of the whole work, thousands of people's personal feelings, truths, hesitations, and confusion come together to know a strong possibility about the origin of the corona virus.