The module focuses on the field of complex networked systems and presents the structure of networks and their dynamics as key concepts across disciplines. Examples of networked systems include the Internet, the World Wide Web, social networks of acquaintance or other connections between individuals, inter-organisational networks, neural networks, metabolic networks, food webs, and many others. There is increasing evidence that such diverse networks share common topological and dynamical features, indicating the existence of robust self-organising principles and evolutionary laws that govern many natural and social systems. The course aims to develop a unified theoretical framework for the analysis of these common properties shared by a wide range of networked systems. This framework will then be used for the discussion of sociologically relevant phenomena that exhibit complex network structures and dynamics, such as epidemics of disease, cultural fads, financial crises, organisational innovation and inter-firm coordination. If public health authorities want to minimise the danger of a viral epidemic, but have limited vaccinations, how should they be distributed throughout the population? If a firm wants to initiate a word-of-mouth campaign for a new product, but can hand out free samples to only a few people, who should they pick? How vulnerable are large infrastructure networks like the power grid or the Internet to random failure or even deliberate attacks? How do new ideas become crazes, or small shocks get blown out of all proportion in the form of cascades throughout a financial system? To address these and many other problems, the course will develop a highly interdisciplinary approach to social science by combining current research literature on complex systems and social networks with contributions of relevant organisational and sociological research.