Living on the Edge: Alternative Network Models for Socio-spatial Analysis in Archaeology

Author(s): Jessica Munson

Year: 2021

Summary

This is an abstract from the "People and Space: Defining Communities and Neighborhoods with Social Network Analysis" session, at the 86th annual meeting of the Society for American Archaeology.

Recent studies using network analysis in archaeology seek to understand the interactions and structures that defined past societies. Such approaches are based on graph theoretic models that are simplifications of reality used to conceptualize and describe relationships, either qualitatively or quantitatively, between a set of components interacting in a social system. The appeal of this approach stems from its explicit emphasis on the relationships between the entities of interest. Frequently, those relationships are inferred based on the assumption that similarity in site assemblages is a proxy for the existence of a tie. This approach, however, runs the risk of circular reasoning if assumptions about the types of ties are not made explicit. Other approaches consider physical location and geographic distance for reconstructing archaeological networks. While the phenomena archaeologists study using networks is inherently both social and spatial, these models rarely take into consideration the broader landscape and natural features on which these processes play out. This paper presents an alternative approach to identify ancient communities based on dendritic network topology. The basic model is described and illustrated with a case study using settlement pattern data recently collected by the Proyecto Arqueológico Altar de Sacrificios from the Upper Usumacinta Confluence Zone.

Cite this Record

Living on the Edge: Alternative Network Models for Socio-spatial Analysis in Archaeology. Jessica Munson. Presented at The 86th Annual Meeting of the Society for American Archaeology. 2021 ( tDAR id: 466581)

Spatial Coverage

min long: -94.197; min lat: 16.004 ; max long: -86.682; max lat: 21.984 ;

Record Identifiers

Abstract Id(s): 31954