Topics being offered in SS23:

NLP (adaptation) for historical texts

• Language models for NLP on historical texts
  
  Starting Paper: MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950) (Manjavacas Arevalo & Fonteyn, NLP4DH 2021)
  
  
• Transfer learning for NER on historical texts
  
  Starting Papers:
  • Transferring Modern Named Entity Recognition to the Historical Domain: How to Take the Step?(Blouin et al., NLP4DH 2021)
  • Batavia asked for advice. Pretrained language models for Named Entity Recognition in historical texts. (Arnoult et al., LaTeCHCLfL 2021)

NLP in literary analysis

• Identification of key paragraphs
  
  Starting Paper:  Lotte and Annette: A Framework for Finding and Exploring Key Passages in Literary Works (Arnold & Jäschke, NLP4DH 2021)
• Data bias in literary classification
  
  Starting Paper:  Measuring the Effects of Bias in Training Data for Literary Classification (Bagga & Piper, LaTeCHCLfL 2020)
• Analysis of translated literature
  
  Starting Papers:  

  • TL-Explorer: A Digital Humanities Tool for Mapping and Analyzing Translated Literature (Zhai et al., LaTeCHCLfL 2020)
  • Translationese in Russian Literary Texts (Kunilovskaya et al., LaTeCHCLfL 2021)