  Red tide blooms of the dinoflagellate Karenia brevis (K. brevis) produce
toxic coastal conditions that can impact marine organisms and human health,
while also affecting local economies. During the extreme Florida red tide event
of 2017-2019, residents and visitors turned to social media platforms to both
receive disaster-related information and communicate their own sentiments and
experiences. This was the first major red tide event since the ubiquitous use
of social media, thus providing unique crowd-sourced reporting of red tide
impacts. We evaluated the spatial and temporal accuracy of red tide topic
activity on Twitter, taking tweet sentiments and user types (e.g. media,
citizens) into consideration, and compared tweet activity with reported red
tide conditions, such as K. brevis cell counts, levels of dead fish and
respiratory irritation on local beaches. The analysis was done on multiple
levels with respect to both locality (e.g., entire Gulf coast, county-level,
city-level, zip code tabulation areas) and temporal frequencies (e.g. daily,
every three days, weekly), resulting in strong correlations between local
per-capita Twitter activity and the actual red tide conditions observed in the
area. Moreover, an association was observed between proximity to the affected
coastal areas and per-capita counts for relevant tweets. Results show that
Twitter is a reliable proxy of the red tide's local impacts and development
over time, which can potentially be used as one of the tools for more efficient
assessment and a more coordinated response to the disaster in real time.

Social and Information Networks;Applications