Sentiment Analysis of Tweets during Covid-19 Lockdown in India

• Published in: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) pp. 1 - 6
• Main Authors: Jindal, Deepanshu, Kumawat, Yash, Sharma, Aditya Kumar, Bisi, Manjubala
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06-07-2023
• Subjects: Analytical models; COVID-19; Deep learning; Lockdown; Machine learning; Natural language processing; Natural languages; NLTK; Pandemics; Sentiment analysis; Social networking (online)
• ISSN: 2473-7674
• DOI: 10.1109/ICCCNT56998.2023.10306581

Sentiment analysis has become most important and most popular field of natural language processing(NLP). Emotions can be extracted out of text using sentiment analysis. Everyone is using social media to receive and communicate different information on a big scale during COVID-19. The evaluation of such type of content is helpful for decision maker authorities. In this work, the sentiments of Indians during Lockdown are analysed using NLP and Machine Learning models. Tweepy API is used to extract data from Twitter and annotation is done using TextBlob and VADER libraries. Data preprocessing is done using NLTK. The experimental results show that Ensemble model with unigram has good performance. After analysing the sentiments of Indians, it is found that major people are in favour of lockdown decision made by the Indian government.