Using the Machine Learning Naive Bayes Algorithms for Sentiment Analysis on Online Product Reviews in the Air of Energy Optimization

Abstract

The purpose of this study was to explore how consumers perceive two of the leading smartphone brands, Samsung and iPhone, using a corpus of tweets. Our approach involved sifting through the tweets to remove any irrelevant content, followed by a sentiment analysis to gain an overall perspective of how each brand was viewed. Our analysis demonstrated that Samsung received a higher proportion of tweets with negative sentiment as compared to iPhone. Moreover, the most common terms in tweets referring to Samsung reflected negative emotions like “concern,” “issue,” and “trouble,” while tweets about iPhone expressed positive emotions such as “like,” “great,” and “best.” These findings have significant implications for marketing research and offer valuable insights for businesses on how they can utilize social media to enhance their brand reputation and image.