Social media has emerged as a critical communication tool in contemporary society, bringing the world closer by making news and opinions more accessible through virtual platforms. Among these, Twitter stands out with over 350 million users worldwide. However, the highly unstructured nature of Twitter data poses significant challenges for analysis. Recently, the rich content of social media networks has spurred extensive research, particularly in light of the COVID-19 pandemic that has impacted global populations. Concurrent with the search for a vaccine, numerous studies have focused on analyzing public sentiment during the crisis, using data from various social media platforms. This study concentrates on people's opinions regarding COVID-19 vaccines, employing several machine learning models to analyze data from Twitter. It was discovered that the most accurate algorithm was the SGD Classifier, which utilized all three n-gram ranges, achieving an accuracy of 0.75.
Key words: Arabic Tweets; COVID-19 Vaccines; Sentiment Analysis; Social Media;Twitter Data
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