A proposed system is focuses on engineering students’ Twitter posts to understand issues and problems in their educational experiences. The proposed scheme is made up of Twitter data extraction, tweets data cleaning. Classification of tweet data and web module .The proposed scheme performs various operations on tweets as shown in Figure 1
Architecture of Proposed System for Mining Twitter Data using ML.
In the first phase user extract tweets from twitter using twitter standard API . Tweet processing operation performed in second phase. Then, tweet classification is perform using Naïve Bayes algorithm, tweets are classified into heavy study load, lack of social engagement, negative emotions, sleep problems, soft-skill issues and other. In data cleaning phase perform various operation on tweet to remove noise from it.