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Antal van den BoschRadboud Universiteit Nijmegen

 a.vandenbosch@let.ru.nl

http://antalvandenbosch.ruhosting.nl/

Marten Düring

Radboud Universiteit Nijmegen

m.during@let.ru.nl

www.research.martenduering.com

MERIT: Machine-based Extraction of Relations In Texts: Multi-perspective Memories from the Dutch Battlefields 1944-1945

Project proposal

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About Marten

2004BA in European Cultural History at University of AugsburgOral history: 1945-1948 in Southwest Germany under French occupation

2006MA in War, History and Memory at University of ManchesterEye-witness testimonies of Coventry 1941 and Dresden 1945

2012PhD in Contemporary History at Kulturwissenschaftliches Institut Essen/University of MainzNetwork analysis of support networks for persecuted Jews during National Socialism

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Interested in software-assisted historical research:

• SNA/ Historical Network Research (fav.: NodeXL)

• Qualitative Data Analysis (MaxQDA)• Agent-based Simulations (Netlogo)• Video Annotations (Elan)

• Natural Language Processing

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• Reduction of complex information

• Abstraction• Standardization• Targeted representation

Main objective: Orientation

See: Lothar Krempel: Visualisierung komplexer Systeme. Grundlagen der Darstellung mehrdimensionaler Netzwerke. Campus Verlag 2005

The purpose of visualizations

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Gleanings from visualizations of difficult data

(1) Filtering

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The Segal family‘s network…

How were they able to make contact with strangers?

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…reduced to brokerage ties only…

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…removed the members of the Segal family.

HelperRefugee

Broker

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(2) Recombining data

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Actors and points in time

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(3) Aggregation of information

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Aggregating data from heterogeneous sources

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Six distinctive support networks?

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Ties among refugees in all 6 networks. Rescue?

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Historical Network Research

https://sites.google.com/site/historicalnetworkresearch/

Bibliography, Newsletter, Conference calendar, Videos

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MERITMachine-based Extraction of Relations In

Texts: Multi-perspective Memories from the Dutch Battlefields 1944-1945

• Radboud University Nijmegen • Bevrijdingsmuseum Groesbeek• Airborne Museum Hartenstein• Storia• Stadsregion Arnhem/Nijmegen

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An example

Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg near Wolfheze in the afternoon of 17th September 1944.

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Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg near Wolfheze in the afternoon of 17th September 1944.

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Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg near Wolfheze in the afternoon of 17th September 1944.

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Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg near Wolfheze in the afternoon of 17th September 1944.

…a German Citroen staff car suddenly appeared at a junction in between the platoon's positions, prompting these units to open fire with rifles and sten guns, killing all inside. So enthusiastic had been the firing that both vehicle and passengers were riddled with bullets and it took Cleminson's intervention to get his men to cease fire. This prize put the platoon on a high.

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Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg in the afternoon of 17th September 1944.

…a German Citroen staff car suddenly appeared at a junction in between the platoon's positions, prompting these units to open fire with rifles and sten guns, killing all inside. So enthusiastic had been the firing that both vehicle and passengers were riddled with bullets and it took Cleminson's intervention to get his men to cease fire. This prize put the platoon on a high.

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Generalmajor Friedrich Kussin and his driver were shot dead on Utrechtseweg near Wolfheze in the afternoon of 17th September 1944.

…a German Citroen staff car suddenly appeared at a junction in between the platoon's positions, prompting these units to open fire with rifles and sten guns, killing all inside. So enthusiastic had been the firing that both vehicle and passengers were riddled with bullets and it took Cleminson's intervention to get his men to cease fire. This prize put the platoon on a high.

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Questions

• Two or four casualties? Where are they?• Why no attempt for arrest?• Where are the many bulletholes? • Why no blood?

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Overall goal for MERIT:

Help historians and curators with the laborious task of finding relevant information by (semi-) automatically linking related sources. Create a basis for interpretation of

– Events– Motifs

Link primary sources, NLP analysis and quantifications.

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1. Aggregate depictions of events based on location, time and type of event.

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1. Aggregate depictions of events based on location, time and type of event.

Event (narrow definition): a set of documented interconnected actions which are identifiable by mentioned points in time and/or a specific location in the Arnhem/Nijmegen area between September 1944 and May 1945.

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1. Aggregate depictions of events based on location, time and type of event.

• Discover multi-faceted descriptions of war experience

• Highlight contradictions and ambiguities of sources and their interpretations. Patterns?

• Knowledge map – who depicts what? Patterns?

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Knowledge map: Mapping events and witnesses

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Knowledge map: Mapping events and witnesses

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Knowledge map: Mapping events and witnesses

• Which events have been documented?

• Identify new, potentially relevant sources

• Raise new questions:– „Why doesn‘t SourceX mention EventY?“– „How do Allied and German war

photography relate?“

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2. Identify and extract motifs from historical sources 1944-2012

Motifs in folk tales:• „evil stepmother“• „ghost summoned by music“

Motifs in our case:• „loud and brutal German soldier“• „fearful German soldier“• „elated Dutch civilians”

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2. Identify and extract motifs from historical sources 1944-2012

• Which motifs constitute Allied, Dutch and German narratives?

• Which motifs constitute retrospective depictions?

• How do they change over time?

• Geographical patterns?

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3. Digital Cultural Heritage

• Augmented reality: Text, photos, video, location today

• Public database for personal queries: a step towards self-curation

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Challenges

• Multilingual sources

• Event recognition

• Heterogeneous, unstructured sources

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Thank you for your attention!