Networks in Archaeology: Phenomena, Abstraction, Representation

Collar, Anna; Coward, Fiona; Brughmans, Tom; Mills, Barbara J.

doi:10.1007/s10816-014-9235-6

Cited by 196 publications

(118 citation statements)

References 30 publications

(12 reference statements)

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“…3.1.4. Eigenvector centrality has been recently applied to 497 archaeological problems (Collar et al, 2015;Gjesfjeld, 2015;Golitko and Feinman, 2015); 498 however, it has been noted that eigenvector centrality, as defined in Eq. (5), can be unstable 499 and produce significantly different results when there are slight changes made to the network 500 (Costenbader and Valente, 2003;Mills et al, 2013;Gjesfjeld, 2015).…”

Section: Choice Of Pagerank Over Other Centrality Measuresmentioning

confidence: 99%

“…In 30 archaeology, there is a burgeoning literature utilising such approaches (see, for e.g. 31 Broodbank, 2000;Brughmans, et al, 2016;Collar et al, 2015;Hage and Harary, 1991; 32 Knappett, 2011 32 Knappett, , 2013. Notably, these have included attempts to define network properties 33 from distributions of archaeological materials such as physical monuments (e.g.…”

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Transport networks and towns in Roman and early medieval England: An application of PageRank to archaeological questions

Brookes

Huynh

2018

Journal of Archaeological Science: Reports

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This paper examines the development of a road network through time to consider 8 its relationship to processes of urbanisation in Roman and early medieval England. 9Using a popular network measure called PageRank, we classify the importance of 10 nodes in the transport network of roads and navigable waterways to assess the 11 relative location of urban places. Applying this measure we show that there is a 12 strong correlation between the status of towns in both Roman and medieval 13 periods and their proximity to transport nodes with high values of PageRank. 14 Comparison between two temporally distinct networks-Early Roman, and that 15 recorded in the Domesday survey of AD 1086-allows for a discussion about the 16 determinants of urban growth at different times. The applicability of PageRank to 17 other forms of network analysis in archaeology are offered in conclusion. (Gross and Sayama, 2009;Lewis, 2009; Wasserman and 26 Faust, 1994) to other fields have yielded interesting results and proven that promising areas 27 of research can emerge (see for e.g. Barabasi and Oltvai, 2004;Barthelemy, 2011; Borgatti et 28 al., 2009;Dunne et al., 2002;Emirbayer and Goodwin, 1994;Glaisyer, 2004; McPherson et al., 29 2001;Proulx et al., 2005;Singh, 2005;Sorenson et al., 2006;Watts and Dodds, 2007). In 30 archaeology, there is a burgeoning literature utilising such approaches (see, for e.g. 31 Broodbank, 2000;Brughmans, et al., 2016;Collar et al., 2015;Hage and Harary, 1991; 32 Knappett, 2011 32 Knappett, , 2013. Notably, these have included attempts to define network properties 33 from distributions of archaeological materials such as physical monuments (e.g. Johansen, et 34 al. 2004), artefacts of known provenance (e.g. Sindbaek, 2007), historically-attested journeys 35 or physical route networks (e.g. Graham 2006;Isaksen, 2008), and other cultural phenomena 36 such as language and legal traditions (e.g. Collar, 2013;Terrell, 2010). 37 38 Relevant to this paper, are works that have applied network analysis to explore the structure 39 of past transport networks. In an early application of this type, Dicks (1972) evaluated the 40 Roman road system of Britain via path ordering. More recently, Orengo and Livarda (2015) 41 have tested the same evidence to demonstrate the relation between the trading activities of 42 towns and the connections of nearby transport links. 43 44 Extending these debates, this paper seeks to demonstrate the applicability of using a popular 45 network measure called PageRank to archaeological questions. An algorithm used by Google 46 Search, PageRank (Brin and Page, 1998) was originally designed as a way of measuring the 47 relative importance of web pages based on the links among them. The intended purpose of 48 such ranking was to filter the web pages and return the most relevant ones in response to a 49 query given to the search engine. However, the algorithm itself is universal and can usefully 50 be applied to other situations where one seeks to identify the importance of entities in a 5...

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Section: Choice Of Pagerank Over Other Centrality Measuresmentioning

confidence: 99%

mentioning

confidence: 99%

Transport networks and towns in Roman and early medieval England: An application of PageRank to archaeological questions

Brookes

Huynh

2018

Journal of Archaeological Science: Reports

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“…Sosna et al 2012;Collar et al 2015) and therefore requires only minimal introduction. Based on the statistical analysis of relationships between different actors, the fundamental concept of SNA is to reveal the underlying socio-structural aspects and social patterns.…”

Section: Network Analysismentioning

confidence: 99%

Chronology and development of the Chalcolithic necropolis of Varna I

Krauß¹,

Schmid

Kirschenheuter³

et al. 2017

Doc. praeh.

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“…Even though it is beyond argument that the number of articles on network applications appeared on archeology journals has been increasing continuously during the last decade (Collar et al, 2015), the fact that a large majority of these were published quite recently, when the big hunt for benchmarks was almost over, may have had a negative impact on the diffusion of these network datasets.…”

Section: At the Periphery Of Network Sciencementioning

confidence: 99%

Wiring the Past: A Network Science Perspective on the Challenge of Archeological Similarity Networks

Prignano

Morer

Dı́az-Guilera

2017

Front. Digit. Humanit.

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Nowadays, it is a common knowledge that scholars from different disciplines, regardless of the specificities of their research domains, can find in network science a valuable ally when tackling complexity. However, there are many difficulties that may arise, starting from the process of mapping a system onto a network which is not by any means a trivial step. This article deals with those issues inherent to the specific challenge of building a network from archeological data, focusing in particular on networks of archeological contexts. More specifically, we address technical difficulties faced when constructing networks of contexts or sites where past interactions are inferred based on some kind of similarity between the corresponding assemblages (Archeological Similarity Networks or ASN). We propose a basic characterization in formal terms of ASN as a well-defined class of networks with its own specific features. Throughout the article, we devote special attention to the problem of quantifying the similarity between sites, especially in relation with the ubiquitous issues of data incompleteness and the reliability of the inferred ties. We argue that, generally speaking, human past studies are quite disconnected from the rest of interdisciplinary applications of network science and that this prevent this field from fully exploiting the potential of such methods. Our goal is to give hints about which are the interesting questions that archeological applications put on the table of network scientists. We suggest that such questions need to be translated into formal terms in order to be properly addressed within the framework of interdisciplinary collaborations. At this aim, a computational experiment is devised as an illustrative example of how simple models can help the cause.

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Networks in Archaeology: Phenomena, Abstraction, Representation

Cited by 196 publications

References 30 publications

Transport networks and towns in Roman and early medieval England: An application of PageRank to archaeological questions

Transport networks and towns in Roman and early medieval England: An application of PageRank to archaeological questions

Chronology and development of the Chalcolithic necropolis of Varna I

Wiring the Past: A Network Science Perspective on the Challenge of Archeological Similarity Networks

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