Altaweel, M;
(2019)
The Market for Heritage: Evidence from eBay using Natural Language Processing.
Social Science Computer Review
10.1177/0894439319871015.
(In press).
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Abstract
The trade in antiquities and cultural objects has proven difficult to understand and yet is highly dynamic. Currently, there are few computational tools that allow researchers to understand the nature of the legal market, which can also potentially provide insights into the illegal market such as types of objects traded and countries trading antiquities. Online sales in antiquities and cultural objects are often unstructured data; relevant cultural affiliations, types, and materials for objects are important for distinguishing what might sell, but these data are rarely organized in a format that makes the quantification of sales a simple process. Additionally, sale locations and the total value of sales are relevant to understanding the focus and size of the market. These data all provide potentially useful insights into how the market in antiquities and cultural objects is developing. Based on this need, this work presents the results of a machine learning approach using natural language processing and dictionary-based searches that investigates relatively low-end but high sales volume objects sold on eBay’s US site, where sales are often international, between October 2018 and May 2019. The use of named entity recognition, using a conditional random field approach, classifies objects based on the cultures in which they come from, what type of objects they are, and what the objects are made of. The results indicate that objects from the UK, affiliated with the Roman period, mostly constituting jewelery, and made of metals sell the most. Other important countries for selling ancient and cultural objects include the United States, Thailand, Germany, and Cyprus. Some countries appear to focus on specific types of objects, such as Egypt being a leader in selling Islamic cultural objects. Overall, the approach and tool used demonstrate that it is possible to monitor the online antiquities and cultural objects market while potentially gaining useful insights into the market. The tool developed is provided as part of this work so that it can be applied for other cases and online sites, where it can be applied in real time or using historical data.
| Type: | Article |
|---|---|
| Title: | The Market for Heritage: Evidence from eBay using Natural Language Processing |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/0894439319871015 |
| Publisher version: | https://doi.org/10.1177/0894439319871015 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Natural language processing, machine learning, name entity recognition, conditional random fields, antiquities, heritage, culture, eBay, dictionaries |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Institute of Archaeology UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Institute of Archaeology > Institute of Archaeology Gordon Square |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10079205 |
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