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DOI: 10.14569/IJACSA.2023.0140504
PDF

Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms

Author 1: Tarun Jain
Author 2: Vivek Kumar Verma
Author 3: Akhilesh Kumar Sharma
Author 4: Bhavna Saini
Author 5: Nishant Purohit
Author 6: Bhavika
Author 7: Hairulnizam Mahdin
Author 8: Masitah Ahmad
Author 9: Rozanawati Darman
Author 10: Su-Cheng Haw
Author 11: Shazlyn Milleana Shaharudin
Author 12: Mohammad Syafwan Arshad

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 5, 2023.

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Abstract: One of the main functions of NLP (Natural Language Processing) is to analyze a sentiment or opinion of the text considered. In this research the objective is to analyze the sentiment in the form of tweets towards the Covid-19 vaccination. In this study, the collected tweets are in the form of a dataset from Kaggle that have been categorized into positive and negative depending on the polarity of the sentiment in that tweet, to visualize the overall situation. The reviews are translated into vector representations using various techniques, including Bag-Of-Words and TF-IDF to ensure the best result. Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. The performance metrics used to test the performance of the models show that Support Vector Machine (SVM) achieved the highest accuracy of 88.7989% among the machine learning models. Compared to the related research papers the highest accuracy obtained using LSTM is 90.59 % and our model has predicted with the highest accuracy of 90.42% using BERT techniques.

Keywords: Covid-19 vaccine; sentiment analysis; machine learning; deep learning; natural language processing

Tarun Jain, Vivek Kumar Verma, Akhilesh Kumar Sharma, Bhavna Saini, Nishant Purohit, Bhavika, Hairulnizam Mahdin, Masitah Ahmad, Rozanawati Darman, Su-Cheng Haw, Shazlyn Milleana Shaharudin and Mohammad Syafwan Arshad, “Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140504

@article{Jain2023,
title = {Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140504},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140504},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Tarun Jain and Vivek Kumar Verma and Akhilesh Kumar Sharma and Bhavna Saini and Nishant Purohit and Bhavika and Hairulnizam Mahdin and Masitah Ahmad and Rozanawati Darman and Su-Cheng Haw and Shazlyn Milleana Shaharudin and Mohammad Syafwan Arshad}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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