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Sentiment Analysis based COVID-19 Vaccine Recommender System | IEEE Conference Publication | IEEE Xplore

Sentiment Analysis based COVID-19 Vaccine Recommender System


Abstract:

"COVID-19 has far-reaching global impacts on health, economics, society, education, politics, and the environment. While vaccines are crucial, the threat persists. Our pa...Show More

Abstract:

"COVID-19 has far-reaching global impacts on health, economics, society, education, politics, and the environment. While vaccines are crucial, the threat persists. Our paper introduces a sentiment-based COVID-19 vaccine recommender system using Twitter data. By applying preprocessing and leveraging a novel CT-BERT_CONVLayerFusion model within a random forest ensemble, we classify tweets into seven sentiment categories. Additionally, we perform aspect-based review categorization. Comparative analysis demonstrates that our approach surpasses state-of-the-art models, achieving superior accuracy, recall, precision, and F1-measure. This advanced method aids in combatting COVID-19 and mitigating vaccine hesitancy by offering personalized vaccine recommendations based on individual concerns."
Date of Conference: 05-08 December 2023
Date Added to IEEE Xplore: 18 January 2024
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Conference Location: Istanbul, Turkiye

References

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