  Label propagation is a heuristic method initially proposed for community
detection in networks, while the method can be adopted also for other types of
network clustering and partitioning. Among all the approaches and techniques
described in this book, label propagation is neither the most accurate nor the
most robust method. It is, however, without doubt one of the simplest and
fastest clustering methods. Label propagation can be implemented with a few
lines of programming code and applied to networks with hundreds of millions of
nodes and edges on a standard computer, which is true only for a handful of
other methods in the literature.
  In this chapter, we present the basic framework of label propagation, review
different advances and extensions of the original method, and highlight its
equivalences with other approaches. We show how label propagation can be used
effectively for large-scale community detection, graph partitioning,
identification of structurally equivalent nodes and other network structures.
We conclude the chapter with a summary of the label propagation methods and
suggestions for future research.
