RWTH Aachen University researchers developed PALADIN, a Pattern Language for Analyzing Disturbances in digital social Networks. PALADIN uses a graph-based model and pattern language to automatically analyze social networks for recurring disturbance patterns. It represents actors, media, artifacts and dependencies in a social network. PALADIN was tested on 10 disturbance patterns over 119 social network instances with over 17,000 individuals. The results showed PALADIN could detect different disturbance patterns and provide insights to network administrators. Future work will focus on interoperability, visualization of multidimensional disturbances, and integrating social network simulation.