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.