Summary:

- The article discusses research conducted by the Moody College of Communication at the University of Texas at Austin on mitigating flood risks.
- The researchers used machine learning and natural language processing techniques to analyze social media posts and news articles during Hurricane Harvey in 2017 to better understand how people communicate about floods and how that information can be used to improve emergency response and disaster preparedness.
- The findings suggest that analyzing social media data can provide valuable insights into public perceptions and concerns during a flood event, which can help emergency management agencies and policymakers develop more effective communication strategies and disaster response plans.