Twitter/X Emotions Analysis on COVID-19 Vaccines: A Journey Through Few-Shot Learnin

Social networks empower individuals to freely share their perspectives on a diverse array of subjects. One such topic is the impact of the coronavirus vaccine in preventing the disease. People have written their varying reviews on this matter through tweets. These reviews would contribute to grasp people's feelings and sentiments about Covid-19 vaccination. One common method employed by businesses to assess sentiment in social data is Sentiment analysis. Our model classifies individuals' perspectives into three labeled data categories: negative, neutral and positive. We have used Few Shot Learning to offer a cost-effective training method, particularly paraphrase-mpnet-base-v2, to improve text classification of the Kaggle-extracted tweet dataset. The findings derived from the experiment suggest that our method has achieved 96.37% accuracy score,, which outperformed previous published works.