Complex Spreading Phenomena in Social Systems

Sune Lehmann is an associate professor at the Technical University of Denmark, an adjunct (full) professor at the University of Copenhagen’s Department of Sociology, and and adjunct associate professor at the Niels Bohr Institute for Theoretical Physics. He’s also associate director of the interdisciplinary "Center for Social Data Science" at the University of Copenhagen. In addition to publishing in top interdisciplinary journals, Prof Lehmann’s work on spreading processes —  including spreading in both biological and social domains — has received world-wide press coverage.Yong-Yeol (YY) Ahn is an assistant professor at Indiana University School of Informatics, Computing, and Engineering. He worked as a postdoctoral research associate at the Center for Complex Network Research at Northeastern University and as a visiting researcher at the Center for Cancer Systems Biology at Dana-Farber Cancer Institute after earning his PhD in Statistical Physics from KAIST in 2008. He has made contributions in a variety of areas including the study of network community structure, information diffusion, and culture. He is a recipient of several awards, including the Microsoft Research Faculty Fellowship and the LinkedIn Economic Graph Challenge.

• 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.