Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …

Network science provides a set of quantitative methods to investigate complex systems,
including human cognition. Although cognitive theories in different domains are strongly …

Liberals claim that globalization has led to fragmentation and decentralized networks of
power relations. This does not explain how states increasingly “weaponize …

This book is a comprehensive introduction to quantitative approaches to complex adaptive
systems. Practically all areas of life on this planet are constantly confronted with complex …

Real-world networks are often claimed to be scale free, meaning that the fraction of nodes
with degree k follows a power law k− α, a pattern with broad implications for the structure …

Networks evolve continuously over time with the addition, deletion, and changing of links
and nodes. Although many networks contain this type of temporal information, the majority of …

Networks are a fundamental tool for understanding and modeling complex systems in
physics, biology, neuroscience, engineering, and social science. Many networks are known …

Graph-structured data arise naturally in many different application domains. By representing
data as graphs, we can capture entities (ie, nodes) as well as their relationships (ie, edges) …

Exactly half a century has passed since the launch of the first documented research project
(1965 Dendral) on computer‐assisted organic synthesis. Many more programs were created …

Increasingly, scholars recognize the importance of understanding supply network
disruptions. However, the literature still lacks a clear conceptualization of a network-level …