Sentiment Analysis for Twitter Tweets: A Framework to Detect Sentiment Using Naïve Bayes Algorithm

In today’s society, people communicate through social media. Digital life has expanded dramatically. Twitter is a social media platform where users can post tweets. The researchers used sentiment analysis, a popular research topic in recent years. Correctly identifying sentiments is critical since it opens up a world of possibilities. The researchers used the Twitter API and the tweepy python module to extract real-time tweets from Twitter. To imprive the rigor of this study, we used a Kaggle dataset to create a model that using Naïve Bayes Algorithm to recognize sentiments better. The researchers also compared different algorithms to identify the best algorithm for the data. In addition, the researchers collected and obtained information from credible sources to assess the trained model’s correctness and reliability. The analysis of the result highlights the implication of our studies.