The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

In the past 15 years, statistical physics has been successful as a framework for modelling
complex networks. On the theoretical side, this approach has unveiled a variety of physical …

Modeling and generating graphs is fundamental for studying networks in biology,
engineering, and social sciences. However, modeling complex distributions over graphs …

Multilayer networks is a rising topic in Network Science which characterizes the structure
and the function of complex systems formed by several interacting networks. Multilayer …

In the past years, network theory has successfully characterized the interaction among the
constituents of a variety of complex systems, ranging from biological to technological, and …

In most natural and engineered systems, a set of entities interact with each other in
complicated patterns that can encompass multiple types of relationships, change in time and …

Throughout the book, we use empirical examples to illustrate the material. Because social
networks are studied in a variety of traditional academic disciplines, we draw our examples …

The classification problem is closely related to the clustering problem discussed in Chaps. 6
and 7. While the clustering problem is that of determining similar groups of data points, the …

Individuals with depressive symptoms are more likely to be isolated in their social networks,
which can further increase their symptoms. Although social interactions are an important …

Business intelligence and analytics (BI&A) has emerged as an important area of study for
both practitioners and researchers, reflecting the magnitude and impact of data-related …