Behavioral Network Science is a book about why and how structure matters in language, mind and society. It explains how to use network science to investigate issues like language evolution, the aging mind, social conflict, and creativity. Inside, readers will find 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 explores 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 an intuitive understanding of how network science can be employed to quantify and generate real phenomena. Accompanying online R code (found here) demonstrates how R is used to create simulations and explore data, allowing readers to replicate all the simulations and figures in the book for themselves. This book is an essential reference for graduate students and researchers in cognitive sciences, behavioral economics, and health and social policy seeking a nuanced understanding of the intersection between network science and behavioral research.