Attention dynamics on social technology platforms in organizations: An empirical study of structural and temporal mechanisms

In an era of digital ubiquity, organizations increasingly face challenges of capturing, managing, and channeling the limited attention of workers. This study examines interdependent patterns of attention allocation on a social technology platform. We collected digital traces and personnel records from a European aviation company and analyzed 56,502 time-stamped communicative events of 3346 workers using bipartite relational event models. The findings show that structural and temporal mechanisms of attention dynamics collectively shape worker engagement on the platform: popular threads are more likely to attract additional attention; workers tend to engage in threads where their colleagues are active; workers revisit threads they have previously participated in; and highly active workers are inclined to contribute to less popular threads. This study offers a conceptual and analytic frame that demonstrates the value of viewing social technology platforms as an interdependent network of workers making decisions as to how to allocate limited attention resources.