Behavioural Network Science provides a comprehensive introduction to network science for social and behavioral researchers and students. It is a self-contained guide to the fundamentals of network science, beginning with principles of representing and making networks, network metrics, and network evolution. It then delves into specific applications of network science to behavioral research including language evolution, learning, memory, aging, creativity, conspiracies, group problem-solving, opinion polarization, and social conflict. Within each application, theoretical aspects surrounding a core problem are discussed, providing readers with an intuitive understanding of how network science can be employed to quantify and generate behavioural phenomena. Accompanying online R code allows readers to replicate simulations and generate figures. This book is an essential reference for graduate students and researchers in cognitive sciences, behavioural economics, and health and social policy seeking a nuanced understanding of the intersection between network science and behavioural research.