Policies and management decisions in the marine environment are driven in part by public sentiment which can grow more intense during hazard events like Harmful Algae Blooms (HABs). The public conversations on social media sites like Twitter (before X) reveal the polarized nature of HABs through nuanced language and sentiment. This article uses mixed methods of machine learned topic modeling and inductive qualitative coding to describe the ways the long-term 2017-2019 Karenia brevis "red tide" bloom were politicized across Florida's South West coast.
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