  Community detection of network flows conventionally assumes one-step dynamics
on the links. For sparse networks and interest in large-scale structures,
longer timescales may be more appropriate. Oppositely, for large networks and
interest in small-scale structures, shorter timescales may be better. However,
current methods for analyzing networks at different timescales require
expensive and often infeasible network reconstructions. To overcome this
problem, we introduce a method that takes advantage of the inner-workings of
the map equation and evades the reconstruction step. This makes it possible to
efficiently analyze large networks at different Markov times with no extra
overhead cost. The method also evades the costly unipartite projection for
identifying flow modules in bipartite networks.
