Thomas T. Hills – författare

Behavioral Network Science explains how and why structure matters in the behavioral sciences. Exploring open questions in language evolution, child language learning, memory search, age-related cognitive decline, creativity, group problem solving, opinion dynamics, conspiracies, and conflict, readers will learn essential behavioral science theory alongside novel network science applications. This book also contains an introductory guide to network science, demonstrating how to turn data into networks, quantify network structure across scales, and hone one's intuition for how structure arises and evolves. Online R code allows readers to explore the data and reproduce all the visualizations and simulations for themselves, empowering them to make contributions of their own. For data scientists interested in gaining a professional understanding of how the behavioral sciences inform network science, or behavioral scientists interested in learning how to apply network science from the ground up, this book is an essential guide.

Behavioral Network Science explains how and why structure matters in the behavioral sciences. Exploring open questions in language evolution, child language learning, memory search, age-related cognitive decline, creativity, group problem solving, opinion dynamics, conspiracies, and conflict, readers will learn essential behavioral science theory alongside novel network science applications. This book also contains an introductory guide to network science, demonstrating how to turn data into networks, quantify network structure across scales, and hone one's intuition for how structure arises and evolves. Online R code allows readers to explore the data and reproduce all the visualizations and simulations for themselves, empowering them to make contributions of their own. For data scientists interested in gaining a professional understanding of how the behavioral sciences inform network science, or behavioral scientists interested in learning how to apply network science from the ground up, this book is an essential guide.

The Cambridge Handbook of Behavioural Data Science offers an essential exploration of how behavioural science and data science converge to study, predict, and explain human, algorithmic, and systemic behaviours. Bringing together scholars from psychology, economics, computer science, engineering, and philosophy, the Handbook presents interdisciplinary perspectives on emerging methods, ethical dilemmas, and real-world applications. Organised into modular parts-Human Behaviour, Algorithmic Behaviour, Systems and Culture, and Applications-it provides readers with a comprehensive, flexible map of the field. Covering topics from cognitive modelling to explainable AI, and from social network analysis to ethics of large language models, the Handbook reflects on both technical innovations and the societal impact of behavioural data, and reinforces concepts in online supplementary materials and videos. The book is an indispensable resource for researchers, students, practitioners, and policymakers who seek to engage critically and constructively with behavioural data in an increasingly digital and algorithmically mediated world.