A Mesoscale Description of Networks' Dynamics Through Continuous Partitioning

Large graphs require effective methods giving an appropriate mesoscopic description. Several approaches exist today to partition (static) graphs into communities (Fortunato, 2010). However, many networks are intrinsically dynamical, and describing them as static networks would cause loss of important informtion (Holme and Saramaki, 2012; Holme 2015). For example, dynamic processes such as the emergence of new scientific disciplines, their fusion, split or death need a mesoscopic description of the evolving network of scientific articles.