Analyzing of premier institution using twitter data on real-time basis

In current scenario, Social media websites provide great action for students to share joy and struggle, event emotion and stress, and seek social support. On various social media sites, students discuss and share their everyday experience in an informal and casual manner. Student's digital footprints provide vast amount of implicit knowledge and a whole new perspective for educational researchers and practitioners to understand student's experiences outside the controlled classroom environment. This understanding can inform institutional decision-making on interventions for at-risk students, improvement of education quality, and thus enhance student recruitment, retention, and success. Twitter is one such popular social media, whose data is highly informative. It presents a Challenge for analysis because of its humongous and disordered nature. In this paper, colleges are been ranked based on single feature, multiple feature and no feature, using two data mining algorithms such as Support Vector Machine (SVM) and Polarity Algorithm.