Looted Art Detector

About

Objective: Identify high priority artworks for provenance research

Description: Online Free Digital Tool

Approach: Automatic text analysis using frequency counts

Note: The frequency counts target textual indicators of UNCERTAINTY, UNRELIABILITY, or ANONYMITY, as well as the possible presence of RED FLAG names related to NAZI-looted art, forced sales and duress sales. The resulting calculations do not signify that an artwork is looted. They simply quantify observations concerning the text for further analysis.

How it works

The user uploads a CSV file that contains provenance texts

Note: The uploaded CSV can contain other information as well - urls, titles, artists, etc. The only requirement is that the CSV also contain one column with the provenance texts.

The program will ask the user to enter the name of the column that contains the provenance text.

The Provenance Text Analyser calculates the number of times key words appear in each provenance text and downloads a CSV named “results.csv”

Note: The results.csv file contains all the original information uploaded by the user PLUS additional columns with word counts.

The user uses his/her own tools to analyse the results.csv.

Recommendations: How to analyse "results.csv"

The Text Analysis provides quantitative indicators for the user to integrate in analysis. Which artworks are most likely to have problematic provenances?

1) Look for HIGH UNCERTAINTY

Recommendation: Create an "Uncertainty Index" (Uncertainty Flags/Word Count) and sort in descending order

Explanation: UNCERTAINTY counts words like "probably, "likely", "maybe", "possibly" and "?"

2) Filter for presence of RED FLAG names and/or HIGH UNRELIABILITY

Red Flag names include Nazi art looters, Jewish collectors known to have been plundered and/or murdered, and dealers involved in at least one looted art claim

Project information

This website was built as part of GLAMhack2021: project page, source code.

See Open Art Data for more information.

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