Social Media Narratives on Vaccination: A Sentiment Analysis in Hindi, Tamil, and English

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Prof. Dr. Sanjay Kumar Bahl

Indus Intenational University

Haroli,  Una, Himachal Pradesh – 174301, India

Abstract

The proliferation of social media platforms has fundamentally reshaped public discourse on vaccination, transcending geographic and linguistic boundaries and enabling instantaneous sharing of both supportive narratives and misconceptions. This study undertakes a comprehensive sentiment analysis across three major language communities in India—Hindi, Tamil, and English—over a 12‑month period (January–December 2024). Utilizing a balanced corpus of 45,000 posts drawn from Twitter, Facebook, and ShareChat, we integrated advanced natural language processing (NLP) techniques with manual thematic coding to capture sentiment polarity, prevailing themes, and culturally nuanced concerns. Specifically, we fine‑tuned a multilingual BERT model and developed custom sentiment lexicons for Hindi and Tamil, yielding an average classification accuracy of 87 % across languages. Our analysis reveals that English‑language discourse is predominantly positive (67 %), with effective debunking by health authorities; Hindi‑language posts display a near-equitable split between positive (48 %) and negative (40 %) sentiments, driven in part by localized religious and political narratives; and Tamil‑language discourse registers the highest negative sentiment (52 %), largely attributed to safety concerns and distrust in centralized messaging. By juxtaposing these findings with the readability and dissemination patterns of clinical trial summaries from the WHO and ICMR, we identify critical gaps in comprehension and trust that vary by linguistic community. The study underscores the imperative for tailored public health communication strategies that leverage community influencers, simplify technical content, and proactively address culturally specific myths. These recommendations aim to inform policymakers, health communicators, and platform designers in crafting more effective, linguistically sensitive interventions to combat vaccine hesitancy and misinformation in multilingual settings.

Keywords

Vaccination sentiment; social media analysis; Hindi; Tamil; English; NLP; vaccine hesitancy.

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