Sentiment Analysis of Social Media Platform Reviews Using the Naïve Bayes Classifier Algorithm

The Covid-19 pandemic has caused significant changes in people's lifestyles which are further strengthened by the rapid development of technology. This resulted increased use internet and accelerated dissemination information through social media platforms. Not only for self-expression, can also be a means communication, information, education, even used as marketing tool. Several platforms have recently been popular widely used, number users is increasing from year to year, each user provide rating review application. To find out public opinion on platforms, sentiment analysis will carried several platform applications Google Play Store, namely Twitter, Instagram Tiktok later material evaluating these applications. In this study, dataset was taken based ratings reviews Store using NBC (Naïve Bayes Classifier) method with Python programming language. Based testing 1000 comment data application, it found that majority gave positive (Twitter 57.2%, 74.1%, 83.9%), negative 42.8%, 25.9%, 16.1%) an accuracy rate 85.6% Twitter 83.6% 84.8%