by Kimberly Lifton
Medieval vernaculars are notoriously tricky for digital humanists to work with because they lack standardized spelling. Especially when using out-of-the-box libraries and software, most Natural Language Processing (NLP) techniques simply do not work well for medieval languages. However, word-to-vector models have the capacity to handle noise like spelling variants when trained on a significant number of words. As part of my PhD project, which examines the representations of Muslims in textual sources during the rise of the Ottomans in the fifteenth century, I have created custom word-to-vector models using Middle French texts. These models capture the constellations of Muslim representations in Middle French texts at the word level. My methodology considers the exploratory potential of word-to-vector models for shaping research questions in a process that Gabor Mihaly Toth has aptly described as “semantic wanderings.”1
„Talking About Muslims in Middle French: The Potential of Word-to-Vector Models for Studying Semantic Relationships in Medieval Languages“ weiterlesen
- Gabor Mihaly Toth, “Women in Early Modern Handwritten News: Random Walks and Semantic Wandering in the Medici Archive,” Journal of Digital History 3.2 (2024). https://journalofdigitalhistory.org/en/article/jnkqqTTKW8km [↩]