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arXiv · 2502.01663

Explainable AI for Sentiment Analysis of Human Metapneumovirus (HMPV) Using XLNet

Md. Shahriar Hossain Apu·Md Saiful Islam·Tanjim Taharat Aurpa
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Abstract

In 2024, the outbreak of Human Metapneumovirus (HMPV) in China, which later spread to the UK and other countries, raised significant public concern. While HMPV typically causes mild symptoms, its effects on vulnerable individuals prompted health authorities to emphasize preventive measures. This paper explores how sentiment analysis can enhance our understanding of public reactions to HMPV by analyzing social media data. We apply transformer models, particularly XLNet, achieving 93.50% accuracy in sentiment classification. Additionally, we use explainable AI (XAI) through SHAP to improve model transparency.

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Md. Shahriar Hossain Apu, Md Saiful Islam, Tanjim Taharat Aurpa. 2025-02-01. Explainable AI for Sentiment Analysis of Human Metapneumovirus (HMPV) Using XLNet. https://arxiv.org/abs/2502.01663

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