# Unveiling Public Perceptions: Machine Learning-Based Sentiment Analysis of COVID-19 Vaccines in India

arXiv: https://arxiv.org/abs/2311.11435 · HTML: https://mlsanity.com/paper/2311.11435/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 37 references that are in the map.
- First posted on arXiv 19 Nov 2023.

## Builds on (most cited first, 4 of 4)

- [A large-scale COVID-19 Twitter chatter dataset for open scientific research -- an international collaboration](https://mlsanity.com/paper/2004.03688/) (2020)
- [Twitter Sentiment Analysis via Bi-sense Emoji Embedding and Attention-based LSTM](https://mlsanity.com/paper/1807.07961/) (2018)
- [One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study](https://mlsanity.com/paper/2209.01675/) (2022)
- [Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining](https://mlsanity.com/paper/1911.12848/) (2019)

## Abstract (arXiv)

In March 2020, the World Health Organisation declared COVID-19 a global pandemic as it spread to nearly every country. By mid-2021, India had introduced three vaccines: Covishield, Covaxin, and Sputnik. To ensure successful vaccination in a densely populated country like India, understanding public sentiment was crucial. Social media, particularly Reddit with over 430 million users, played a vital role in disseminating information. This study employs data mining techniques to analyze Reddit data and gauge Indian sentiments towards COVID-19 vaccines. Using Python's Text Blob library, comments are annotated to assess general sentiments. Results show that most Reddit users in India expressed neutrality about vaccination, posing a challenge for the Indian government's efforts to vaccinate a significant portion of the population.