Emotional Catalysts and Dynamic Networks: A Computational Analysis of Mobilization in Digital Activism

The murder of George Floyd served as a focusing event, an unexpected and tragic incident that captured public attention and reoriented ongoing discourse. In communication theory, such events often catalyze rapid agenda shifts and heightened collective expression, particularly within the digital public. This study investigates both structural and content-level transformations in information diffusion on Twitter before and after the event. Results indicate that: (1) user engagement intensified post-event; tweets exhibited increased expressions of anger and sadness, and users who entered the conversation afterward were more responsive to emotionally charged narratives; (2) the underlying social network became more centralized, shifting from decentralized user-to-user interactions to an influencer-driven broadcast model; and (3) despite this centralization, weak unidirectional ties across community boundaries played a critical role in bridging structural holes, enabling the wide dissemination of grievance-oriented, high-intensity emotional content, often framed diagnostically. Building on these findings, the study identifies a dual-pathway model of affective diffusion: weak ties maximize emotional reach by spreading high-arousal messages across communities, while strong ties consolidate motivational framing. Together, these findings suggest that focusing events amplify user engagement and fundamentally reshape the structural and affective dynamics of online information diffusion, embedding emotional expression within the network's topology.