| Title | Sentiment Analysis of Covid19 Vaccines Tweets Using NLP and Machine Learning Classifiers |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Rawat, Amarjeet, Maheshwari, Himani, Khanduja, Manisha, Kumar, Rajiv, Memoria, Minakshi, Kumar, Sanjeev |
| Conference Name | 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON) |
| Keywords | Bit error rate, Blogs, composability, COVID-19, machine learning, machine learning algorithms, natural language processing, privacy, pubcrawl, resilience, Resiliency, sentiment analysis, social networking (online), Spacy, Support Vector Classification |
| Abstract | Sentiment Analysis (SA) is an approach for detecting subjective information such as thoughts, outlooks, reactions, and emotional state. The majority of previous SA work treats it as a text-classification problem that requires labelled input to train the model. However, obtaining a tagged dataset is difficult. We will have to do it by hand the majority of the time. Another concern is that the absence of sufficient cross-domain portability creates challenging situation to reuse same-labelled data across applications. As a result, we will have to manually classify data for each domain. This research work applies sentiment analysis to evaluate the entire vaccine twitter dataset. The work involves the lexicon analysis using NLP libraries like neattext, textblob and multi class classification using BERT. This word evaluates and compares the results of the machine learning algorithms. |
| DOI | 10.1109/COM-IT-CON54601.2022.9850629 |
| Citation Key | rawat_sentiment_2022 |
Sentiment Analysis of Covid19 Vaccines Tweets Using NLP and Machine Learning Classifiers