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.

Part 1: Introduction to spreading in social systems.- Complex contagions: A decade in review.- A simple person's approach to understanding the contagion condition for spreading processes on generalized random networks.- Challenges to estimating contagion effects from observational data.- Part 2: Models and Theories.- Slightly generalized Generalized Contagion: Unifying simple models of biological and social spreading.- Message-passing methods for complex contagions.- Optimal modularity in complex contagion.- Probing empirical contact networks by simulation of spreading dynamics.- Theories for influencer identification in complex networks.- Part 3: Observational studies.- Service adoption spreading in online social networks.- Misinformation spreading on Facebook.- Scalable detection of viral memes from diffusion patterns.- Attention on weak ties in social and communication networks.- Measuring social spam and the effect of bots on information diffusion in social media.- Network happiness: how online social interactions relate to our well being.- Information spreading during emergencies and anomalous events.- Part 4: Controlled studies.- Randomized Experiments to detect and estimate social influence.- The rippling effect of social influence via phone communication network.- Network experiments through academic-industry collaboration.-Spreading in Social Systems: Reflections.