Abstract
The antiquities market repeatedly raises concerns about money laundering, forgeries, and illicit trafficking. Auction houses’ and dealers’ roles in these activities are heavily studied, but there has been little research looking at connections between these market participants. We show the potential for social network analysis illuminate new aspects of the art market. In this case study, we track 30,000 individual items based on catalogued provenance information indicating their prior transit through various auction houses and dealers. The network inferred from these data allows us to address basic questions about the structure of the antiquities market, such as the rate of transit for items in the market, the pathways taken by items between auction houses, and the relationship between sale outcomes and re-appearance at auction. There are two types of objects that reappear at auction: those that failed to sell and are re-auctioned very quickly, and those that are held by a collector for about a decade before returning to auction. We also show that private dealers play a relatively important role in “vetting” certain objects, lending them legitimacy. Finally, we discuss additional uses of social network analysis and possible data sources for future art market researchers.
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Notes
- 1.
These were the most recently available data during the data collection phase of this project.
- 2.
We use the word provenance when referring to an object’s ownership history because that is the term used in auction house catalogues. There is a scholarly debate regarding the appropriate terms to denote an archaeological object’s ownership history since excavation vis-à-vis its archaeological and stratigraphic context or its history since creation. See Gerstenblith (2020) for a history of this debate and the related complexities of an object’s legality and authenticity.
- 3.
An edgearray dataset allows for visualisation of networks by type of relationship by structuring data as a series of stacked matrices that account for multiple levels of relationships at once (Borgatti et al., 2013).
- 4.
Both variables looking at auction house and/or location movement include four categories with values 0–4 in ascending order: (0) item not auctioned, (1) no change in the house and location, (2) a change in the house with no change in the location (e.g., an item is auctioned at Bonhams in London and is then auctioned at Christie’s in London the next time) (3) a change in the location with no change in the house (e.g., an item is auctioned at Bonhams Knightsbridge and then Bonhams New Bond Street), and (4) a change in both the house and the location.
- 5.
NetDraw is a free social network analysis visualisation software that was developed to work alongside the analytical software UCINET. For more information, see http://www.analytictech.com/products.htm.
- 6.
UCINET is a windows-based software package for analysing social networks, developed by Lin Freeman, Martin Everett and Steve Borgatti. For more information, see https://sites.google.com/site/ucinetsoftware/home.
- 7.
A few black dots represent locations such as Christie’s Paris, which does not normally hold stand-alone antiquities auctions. The presence of these nodes is because they sold antiquities in other auctions, and those antiquities later sold at one of the major antiquities auctions from which we gathered data.
- 8.
We partly focus on just 20 because they are identifiable as dealers (provenance information is not always clear on whether someone was a dealer or collector, or what the full name of the dealer is). We also focus on these 20 because they are highly prominent and therefore presumably lend some credibility to the object’s authenticity and may add prestige to the object itself. We ignore items that were noted to have been in a dealer’s private collection, as dealers can act as collectors in their own right.
- 9.
A documented archaeological origin is referred to as provenience, as opposed to provenance, which is a history of the object since excavation. The distinction is important when considering objects’ scientific value, as opposed to just aesthetic value or legality. Regardless of how far back provenance research can track an object, most of the time they still come to the market with no provenience. The foundational studies are Muscarella (1977) and Chippindale and Gill (1993).
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Fabiani, M.D., Marrone, J.V. (2021). Transiting Through the Antiquities Market. In: Oosterman, N., Yates, D. (eds) Crime and Art. Studies in Art, Heritage, Law and the Market, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-84856-9_2
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