Classification of the respiratory infection vaccination tweets using fuzzy logic and deep learning

Respiratory diseases are contagious and immensely affect all aspects of people and spread through the air or direct contact. COVID-19 is one of the most dangerous respiratory infections, and it has exaggerated many countries. The battle to curb its spread was waged in every country, even with few or no infections. Vaccination is one of the most vital to fight against COVID-19, and it started in India in January 2021. Every country's government has created awareness programs about COVID-19 and its updates through messages and videos on social media to reduce misconceptions and panic that followed due to the outright misinformation about COVID-19 and its impacts. This study classifies the medical vaccination tweets related to COVID-19; we extracted the tweets regarding vaccination in India from 1 January 2021 to 31 December 2021. We classified the tweets into four categories: pro-vaccine, anti-vaccine, hesitancy and cognizant. We performed the text summarization using fuzzy logic and classification using the stacked ANN and compared the results using the different word embedding models. During the vaccination period, we identified that allergy is a general topic discussed by individuals in social media through quadratic discriminant analysis. The proposed model surpassed the results of the baseline models and achieved an accuracy of 96.7%.