Recent outrageous posts on social media have taken the globe by storm and have led to diverse views and views of the general public. Social media plays a significant act for or against a government or a corporation that simply can’t decide the movement of market but to grasp the sentiment of twitter data that are posted on social media with good method could be a supreme necessity. It will analyse some twitter postings to grasp human semantic. In any tweet intended posting there are some downgraded keyword. At last, a data-set is ready that consists of unique words collected from twitter posts or comments and so the data-set is trained using Naive Bayes algorithm supported with applied mathematics to spot the sentiment given during a new call and comment . They are going to extract each word of the posting and so it'll be matched by virtue with the data-set words for dilution. Finally, it will be tested to their algorithm using numerous post from twitter that can deliver the result with good accuracy.