Publication

Abstract : This study employs text mining and natural language processing approaches for analyzing and unearthing public discourse and sentiment toward the recent spiking Measles outbreaks reported across the globe. A detailed qualitative study was designed using text mining and natural language processing on the user-generated comments from Reddit, a social news aggregation and discussion website. A detailed analysis using topic modeling and sentiment analysis on Reddit comments (n = 87203) posted between October 1 and December 15, 2022, was conducted. Topic modeling was used to leverage significant themes related to the Measles health emergency and public discourse; the sentiment analysis was performed to check how the general public responded to different aspects of the outbreak. Our results revealed several intriguing and helpful themes, including parental concerns, anti-vaxxer discussions, and measles symptoms from the user-generated content. The results further confirm that even though there have been administrative interventions to promote vaccinations that affirm the parents’ concerns to a greater extent, the anti-vaccination or vaccine hesitancy prevalent in the general public reduces the effect of such intercessions. Proactively analyzing public discourse and sentiments during health emergencies and disease outbreaks is vital. This study effectively explored public perceptions and sentiments to assist health policy researchers and stakeholders in making informed data-driven decisions.