Network Science in Archaeology

Tom Brughmans · Matthew A. Peeples

thg 4 2023 · Cambridge University Press

Giới thiệu về sách điện tử này

The Cambridge Manual to Archaeological Network Science provides the first comprehensive guide to a field of research that has firmly established itself within archaeological practice in recent years. Network science methods are commonly used to explore big archaeological datasets and are essential for the formal study of past relational phenomena: social networks, transport systems, communication, and exchange. The volume offers a step-by-step description of network science methods and explores its theoretical foundations and applications in archaeological research, which are elaborately illustrated with archaeological examples. It also covers a vast range of network science techniques that can enhance archaeological research, including network data collection and management, exploratory network analysis, sampling issues and sensitivity analysis, spatial networks, and network visualisation. An essential reference handbook for both beginning and experienced archaeological network researchers, the volume includes boxes with definitions, boxed examples, exercises, and online supplementary learning and teaching materials.

Giới thiệu tác giả

Tom Brughmans is Associate Professor of Classical Archaeology at the Centre for Urban Network Evolutions, Aarhus University. His research explores how social networks connected people throughout history, how large integrated economies like the Roman Empire could function for centuries, and how expansive communication systems using fire and smoke signaling worked.

Matthew A. Peeples is Associate Professor of Anthropology in the School of Human Evolution and Social Change, and Director of the Center for Archaeology and Society at Arizona State University. His research focuses on integrating archaeological data with methods and models from the broader social sciences to address questions regarding the nature of human social networks over the long term.