A Framework for Reconstructing Archaeological Networks Using Exponential Random Graph Models
Bibliographic Data
| ID | 12426666 |
|---|---|
| Authors | Amati (0000-0003-1190-1237, ETH Zurich, corresponding author), Angus Mol (0000-0001-5448-3712, Leiden University), Termeh Shafie (0000-0002-8419-8477, University of Manchester), C L Hofman (0000-0003-4447-5019, Leiden University), Corinne Hofman, Ulrik Brandes (0000-0002-1520-0430, ETH Zurich) |
| Year | 2019 |
| Volume | 27 |
| Issue | 2 |
| Pages | 192-219 |
| Publication date | 2019-08-19 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Archaeological Method and Theory (JOURNAL) |
| Journal identifiers | ISSN: 1072-5369 • E-ISSN: 1573-7764 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.1007/s10816-019-09423-z |
| PMID | 32508485 |
| OpenAlex | W2965612410 |
| Language | EN |
| Citations received | 10 |
| References cited | 55 |
Reconstructing ties between archaeological contexts may contribute to explain and describe a variety of past social phenomena. Several models have been formulated to infer the structure of such archaeological networks. The applicability of these models in diverse archaeological contexts is limited by the restricted set of assumptions that fully determine the mathematical formulation of the models and are often articulated on a dyadic basis. Here, we present a general framework in which we combine exponential random graph models with archaeological substantiations of mechanisms that may be responsible for network formation. This framework may be applied to infer the structure of ancient networks in a large variety of archaeological settings. We use data collected over a set of sites in the Caribbean during the period AD 100-400 to illustrate the steps to obtain a network reconstruction
Archaeological evidence · Archaeology · Exponential random graph models · Graph · Random graph · Set (abstract data type · Variety (cybernetics · Archaeology and ancient environmental studies · Complex Network Analysis Techniques · Computer Science · Crime, Illicit Activities, and Governance · History · Artificial Intelligence · Theoretical Computer Science
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| Unique citing works | 10 |
|---|---|
| Citations per year | 2 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |