From Showers to Hurricanes: A Typology of Media Storms

Media storms–dramatic outbursts of attention to a story–are key components of media dynamics and the attention landscape. Despite their importance, systematic empirical research on these phenomena has been limited by the constraints of manual content analysis. While various studies offer different descriptions and findings, we still lack a comprehensive understanding of storm types, and how varied dynamics correspond to diverging media effects and contextual impacts. This paper proposes a data-driven typology of media storm based on their structures, addressing this gap. Building upon media storm data previously identified in two decades of U.S. news coverage, we use a semi-supervised method to identify the news articles relating to each instance and apply time-series clustering to categorize them into three distinct types: Dominant Plateaus, Explosive Outbursts, and Slow Boils. We then validate this typology and examine its theoretical implications through three key perspectives drawn from previous research on media storms: issue-attention dynamics, media production environments, and elite actor engagement. We claim that this data-driven typology forms a robust foundation for future research exploring media storms’ varied effects on public discourse and agenda-setting and perhaps even predicting their dynamics.