Investigating the Illicit Trade of Cultural Property with an Automated Data Pipeline Architecture

Abstract

The scale of global art crime has been difficult to quantify due to the vast number of transactions and varying methods of trade. Although online marketplace platforms such as eBay offer promising data to study and track this illicit market, this relationship has not been systematically studied due to the highly technical nature of compiling and wrangling these data. This research project partners with the Cultural Resilience Informatics and Analysis (CURIA) Lab to design a robust data pipeline that collects, processes, and stores data from eBay to quantify and analyze the network mobility of illicit cultural property. The data pipeline consists of a template for accessing eBay's API, understanding API documentation, and collecting necessary features for network analysis. This process represents the first data pipeline architecture to our knowledge that collects data from listings across categories of interest, and stores features in a SQLite database through an automated, recursive script for social science research. The metadata for building and maintaining the data pipeline is recorded in an in-depth guide. The result of this data pipeline framework is a replicable blueprint for interacting with an online marketplace's API environment. This project will act as a precursor to begin research regarding the global trade of illicit cultural property through subsequent network and spatial analysis.