Analisis Sentimen Pembelajaran Campuran Menggunakan Twitter Data

Abstract
Mixed learning methodologies have been disputed in terms of educational quality when it comes to self-study. Educators face specific challenges when making hybrid learning work since they must adjust to teaching while also strengthening their technological abilities. The blended learning paradigm, which is commonly adopted in many educational institutions, can produce a slew of issues for students. The goal of this essay is to gather thoughts about distance learning based on social media comments. This study creates a classification model using Twitter tweet data by assessing public perceptions and acceptance of the mixed learning model. The findings of examining thoughts regarding this model include categorizing tweets as favorable or unfavorable using the Twitter sentiment analysis approach. The results revealed an almost equal polarization of positive and negative sentiments, with 44.51 percent positive and 45.80 percent negative. More research can be done to analyze attitudes not just on Twitter but also on other social media platforms to improve public opinion accuracy about mixed learning in a pandemic crisis.