Triadic balance and network evolution in predictive models of signed networks.

This paper introduces a novel approach for identifying dynamic triadic transformation processes, applied to five networks: three undirected and two directed. Our method significantly enhances the prediction accuracy of network ties. While balance theory offers insights into evolving patterns of triadic structures, its effects on overall network dynamics remain underexplored.