  Product-related reviews are based on users' experiences that are mostly
shared on videos in YouTube. It is the second most popular website globally in
2021. People prefer to watch videos on recently released products prior to
purchasing, in order to gather overall feedback and make worthy decisions.
These videos are created by vloggers who are enthusiastic about technical
materials and feedback is usually placed by experienced users of the product or
its brand. Analyzing the sentiment of the user reviews gives useful insights
into the product in general. This study is focused on three smartphone reviews,
namely, Apple iPhone 13, Google Pixel 6, and Samsung Galaxy S21 which were
released in 2021. VADER, which is a lexicon and rule-based sentiment analysis
tool was used to classify each comment to its appropriate positive or negative
orientation. All three smartphones show a positive sentiment from the users'
perspective and iPhone 13 has the highest number of positive reviews. The
resulting models have been tested using N\"aive Bayes, Decision Tree, and
Support Vector Machine. Among these three classifiers, Support Vector Machine
shows higher accuracies and F1-scores.
