Presentation description

My research analyzes public responses to COVID-19 crisis communication, focusing on distinguishing emotional and logical responses using machine learning. I developed a classifier using linguistic features like LIWC categories and sarcasm markers to categorize tweets as emotional reactions or logical discussions. The goal is to improve crisis communication strategies by understanding how different responses, influenced by source credibility and content, impact public trust and behavior.