  Real-world networks have a complex topology comprising many elements often
structured into communities. Revealing these communities helps researchers
uncover the organizational and functional structure of the system that the
network represents. However, detecting community structures in complex networks
requires selecting a community detection method among a multitude of
alternatives with different network representations, community interpretations,
and underlying mechanisms. This review and tutorial focuses on a popular
community detection method called the map equation and its search algorithm
Infomap. The map equation framework for community detection describes
communities by analyzing dynamic processes on the network. Thanks to its
flexibility, the map equation provides extensions that can incorporate various
assumptions about network structure and dynamics. To help decide if the map
equation is a suitable community detection method for a given complex system
and problem at hand -- and which variant to choose -- we review the map
equation's theoretical framework and guide users in applying the map equation
to various research problems.
