This text is about spreading of information and influence in complex networks. Although
previously considered similar and modeled in parallel approaches there is now experimental
evidence that epidemic and social spreading work in subtly different ways. While previously
explored through modeling there is currently an explosion of work on revealing the mechanisms
underlying complex contagion based on big data and data-driven approaches. This volume consists
of four parts. Part 1 is an Introduction providing an accessible summary of the state of the
art. Part 2 provides an overview of the central theoretical developments in the field. Part 3
describes the empirical work on observing spreading processes in real-world networks. Finally
Part 4 goes into detail with recent and exciting new developments: dedicated studies designed
to measure specific aspects of the spreading processes often using randomized control trials
to isolate the network effect from confounders such as homophily. Each contribution is
authored by leading experts in the field. This volume though based on technical selections of
the most important results on complex spreading remains quite accessible to the newly
interested. The main benefit to the reader is that the topics are carefully structured to take
the novice to the level of expert on the topic of social spreading processes. This book will be
of great importance to a wide field: from researchers in physics computer science and
sociology to professionals in public policy and public health.
