This research explores the factors contributing to information sensitivity in debt markets, focusing on the potential influences of uncertainty, economic performance, and journalist-dependent language. Building upon the foundational work of Dang et al. (Ignorance, debt and financial crises. Yale University Unpublished Working Paper, 2018), we analyze the mechanisms underlying the transition from information-insensitive to information-sensitive states—a shift with implications for potential financial crises. Leveraging machine learning techniques and daily data on variables such as default probability, information acquisition, and newspaper articles, we discern specific narrative triggers embedded within the news. Our analysis underscores the pivotal role of economic states and journalist language in inducing information sensitivity—a phenomenon intricately tied to different psychological thinking processes.