Lack of accuracy in ascertaining nature of users based on Naive Bayes algorithm comparing K-means algorithm

Gaining an understanding of a huge amount of data in order to determine how complex a user information is a process. To identify user-natural activities in social media platforms, a variety of data mining research approaches (such as clustering, sorting, regression, and so on) can be applied. Social media cannot function without users since they enable critical data to be assessed based on either favorable or unfavorable interpretations of the information gathered. We make an effort to explain the conclusions drawn from Twitter analytics. A tweet on Twitter can only include 140 characters; the user can contribute additional information by utilizing URLs and hashtags. The earlier approaches failed to accurately identify the user type, were unreliable, and had low accuracy rates. The process was made to find out the nature of consumers through simple algorithmic experiments.