The SARS-CoV-2 virus, which caused the global COVID-19 pandemic, necessitated a significant worldwide response, with vaccination being a primary strategy. This dissertation explores the public sentiment towards New Zealand’s national vaccination campaign, through a machine learning analysis of large-scale text data gathered from the social media platform Twitter. Focusing on responses from both adults and children, this research aimed to assess the efficacy of health communication strategies and the wider acceptance of the vaccine within the community. The findings underscore a considerable disparity between policy decisions and public sentiment on Twitter, with a significant portion of the New Zealand population expressing negative views on vaccinations. Overall, this research reveals the need for enhanced public engagement, better communication, and more effective use of social media data by policymakers and healthcare professionals in order to address public concerns, mitigate fears, dispel misinformation, and ultimately increase vaccine uptake.