Networks Matter

The book provides unified, practical modeling language links graphs, dynamics, statistics, and machine learning to analyze and explain how networks work across disciplines and scales. This textbook explores the intersection of network science and data science. Tailored for an interdisciplinary audience, it provides a gentle introduction to the fundamentals of mathematical modeling and network analysis, integrating graph and systems theory within a unified notational framework. Networks are considered across a wide range of scientific domains and presented as both real-world phenomena and powerful mathematical tools.

From molecules in a cell to social interactions on media platforms, the book illustrates the broad applicability of network modeling through examples drawn from diverse scientific settings. In doing so, it instills an appreciation for robust theoretical frameworks. No specialized background in mathematics, physics, or engineering is assumed. Aimed at a broad audience, including students in both bachelor's and master's programs, the text is well suited for readers in the life sciences, social sciences, and the natural, physical, and engineering sciences. Whether you are a biologist, engineer, or computer scientist, interested in interconnected systems, this book offers a gateway to understanding the language of networks in an increasingly connected world.