Who’s that lady? — Applying open source intelligence in a history context

During a network analysis of the Dutch astronomer and psychologist Rebekka Aleida Biegel (1886-1943), we stumbled upon an often investigated group photo that most likely shows two of her close friends and a third woman posing with Albert Einstein among others in a chemistry laboratory in Zurich while having a tea party. Using data from the Dark Web, face recognition, open source intelligence (OSINT) tools, and artificial intelligence (AI) techniques, we found in total four group portraits of this gathering and were able to determine the true identities of the three women, as well as one of the unknown men in one of the photos, with a very high degree of certainty. Moreover, we determined the exact day and time the photographs were taken: June 30, 1913 around 4:30 PM. After more than a century, the many riddles surrounding these group photos have been solved. By resolving the many questions regarding the (material) historical context of this iconic photograph of Einstein, three years before he published his theory of relativity, new light has been shed on one of the most exciting periods in the history of science. Our innovative research methodology-including AI, Dark Web, and OSINT-enabled us to reconstruct elements of the past of these totally forgotten and heavily marginalized women from many and diverse scattered and unassuming sources and revealed that their place in the history of physics is even more significant than thought. They, too, were part of Einstein's huge sounding board in the form of his weekly colloquium and had precise astrophysical calculations to add; an indispensible ingredient for proving Einstein's theory of relativity.

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Publication Details

Journal
Endeavour
Published
2024-12-01
DOI
https://doi.org/10.1016/j.endeavour.2024.100967
Citations
41
Primary Topic
Internet Traffic Analysis and Secure E-voting
Type
article
Field-Weighted Citation Impact
14.24
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article

Who’s that lady? — Applying open source intelligence in a history context

Jacques Dane, C. Verhoef
41 citations
Endeavour
Internet Traffic Analysis and Secure E-voting
14.24
article

Who’s that lady? — Applying open source intelligence in a history context

Jacques Dane, C. Verhoef
article en
41 citations

Abstract

During a network analysis of the Dutch astronomer and psychologist Rebekka Aleida Biegel (1886-1943), we stumbled upon an often investigated group photo that most likely shows two of her close friends and a third woman posing with Albert Einstein among others in a chemistry laboratory in Zurich while having a tea party. Using data from the Dark Web, face recognition, open source intelligence (OSINT) tools, and artificial intelligence (AI) techniques, we found in total four group portraits of this gathering and were able to determine the true identities of the three women, as well as one of the unknown men in one of the photos, with a very high degree of certainty. Moreover, we determined the exact day and time the photographs were taken: June 30, 1913 around 4:30 PM. After more than a century, the many riddles surrounding these group photos have been solved. By resolving the many questions regarding the (material) historical context of this iconic photograph of Einstein, three years before he published his theory of relativity, new light has been shed on one of the most exciting periods in the history of science. Our innovative research methodology-including AI, Dark Web, and OSINT-enabled us to reconstruct elements of the past of these totally forgotten and heavily marginalized women from many and diverse scattered and unassuming sources and revealed that their place in the history of physics is even more significant than thought. They, too, were part of Einstein's huge sounding board in the form of his weekly colloquium and had precise astrophysical calculations to add; an indispensible ingredient for proving Einstein's theory of relativity.

EndeavourVol. 48(4)
Rijksmuseum (NL), Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
Gender equality
Openalex Percentile: Top 1%
Internet Traffic Analysis and Secure E-voting
14.24
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