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Temporal networks is a book category focused on systems whose connections change over time—extending traditional network science to capture when interactions occur, how long they last, and in what order. Titles in this genre introduce key concepts such as time-stamped edges, time-respecting paths, burstiness, memory effects, temporal motifs, and dynamic communities, alongside methods for data collection, modeling, visualization, and simulation. Readers will find theoretical foundations, algorithms, and metrics tailored to evolving graphs, as well as case studies across epidemiology and contagion, social and communication networks, human mobility, neuroscience, ecology, infrastructure, and finance. The category includes textbooks, research monographs, and handbooks that bridge physics, computer science, applied mathematics, and the social and life sciences, helping scholars and practitioners analyze, predict, and control processes on time-varying networks.

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