Public Perceptions of HPV Vaccination Through Transformer-Based Social Media Sentiment Analysis
Abstract
Public perception plays a crucial role in determining the success of vaccination programs, particularly for the human papillomavirus vaccine aimed at preventing cervical cancer. Despite the increasing implementation of vaccination initiatives, public opinions expressed in digital environments may influence the acceptance and effectiveness of such programs. This study aims to examine public sentiment toward the human papillomavirus vaccine by analyzing discussions on a social media platform widely used for public communication. A data mining framework was employed to guide the analytical process, including data collection, preprocessing, sentiment classification, and thematic exploration. Transformer-based language models were utilized to classify public sentiment expressed in social media posts, followed by topic modeling to identify key issues discussed by users. The findings reveal that public discourse is largely characterized by supportive attitudes toward vaccination, reflecting a growing awareness of its role in cervical cancer prevention. Nevertheless, several concerns related to vaccine cost, accessibility, and post-vaccination experiences continue to emerge in online discussions. These results highlight the importance of integrating digital discourse analysis into public health communication strategies in order to better understand societal perspectives and improve the effectiveness of vaccination programs.
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