Abstract— The Covid-19 pandemic has caused significant
changes in people's lifestyles which are further strengthened by
the rapid development of technology. This has resulted in
increased use of the internet and accelerated dissemination of

information through social media platforms. Not only for self-
expression, social media can also be a means of communication,

information, education, and even used as a marketing tool. Several
social media platforms have recently been popular and widely
used, the number of users is increasing from year to year, and each
user can provide a rating review of the application. To find out
public opinion on social media platforms, sentiment analysis will
be carried out on several social media platform applications on the
Google Play Store, namely Twitter, Instagram and Tiktok which
will later be used as material for evaluating these applications. In
this study, the dataset was taken based on ratings from user
reviews on the Google Play Store using the NBC (Naïve Bayes
Classifier) method with the Python programming language. Based
on testing of 1000 comment review data from each application, it
was found that the majority gave positive sentiment (Twitter
57.2%, Instagram 74.1%, Tiktok 83.9%), and negative sentiment
(Twitter 42.8%, Instagram 25.9%, Tiktok 16.1%) with an
accuracy rate of 85.6% for the Twitter application, 83.6% for the
Instagram application, and 84.8% for the Tiktok application.