Random graph models are probability distributions that model the structure of a network. These models are commonly applied to test hypotheses concerning the characteristics that might have led to an observed network, and generate networks according to different processes of tie formation. In this chapter, I discuss the application of random graph models to the study of past networks. After a brief introduction to random graph models, I describe how these models can contribute to enhancing archaeological network analyses by complementing the standard descriptive analysis often performed in archaeological studies. I also discuss the limits of these methods and the challenges that archaeologists must meet to apply random graph models in different archaeological contexts.
Amati, V. (2023). Random Graph Models. In T. Brughmans, B.J. Mills, J. Munson, M.A. Peeples (a cura di), The Oxford Handbook of Archaeological Network Research (pp. 294-308). Oxford University Press [10.1093/oxfordhb/9780198854265.013.17].
Random Graph Models
Amati, Viviana
2023
Abstract
Random graph models are probability distributions that model the structure of a network. These models are commonly applied to test hypotheses concerning the characteristics that might have led to an observed network, and generate networks according to different processes of tie formation. In this chapter, I discuss the application of random graph models to the study of past networks. After a brief introduction to random graph models, I describe how these models can contribute to enhancing archaeological network analyses by complementing the standard descriptive analysis often performed in archaeological studies. I also discuss the limits of these methods and the challenges that archaeologists must meet to apply random graph models in different archaeological contexts.
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