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Network Analysis is a category of books focused on understanding the structure and behavior of interconnected systems—such as social, technological, biological, and economic networks—by modeling them as nodes and links. These works cover foundational graph theory and statistics, core measures (e.g., centrality, clustering, paths), algorithms for community detection and link prediction, and models of diffusion, contagion, and network robustness. Many titles address data collection and cleaning, visualization, and computational techniques for large-scale, temporal, and multilayer networks. The category includes textbooks, practical guides, and case studies that apply methods to problems like mapping social influence, tracking epidemics, optimizing infrastructure, and analyzing information flow. It serves readers across data science, sociology, computer science, physics, public health, and economics who seek both theoretical grounding and applied tools.

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