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Abstract
Automated approaches to identifying authorship of a text have become commonplace in the stylometric studies. The current article applies an unsupervised stylometric approach on Middle English documents using the script Stylo in R, in an attempt to distinguish between texts from different dialectal areas. The approach is based on the distribution of character 3-grams generated from the texts of the corpus of Middle English Local Documents (MELD). The article adopts the middle ground in the study of Middle English spelling variation, between the concept of relational linguistic space and the real linguistic continuum of medieval England. Stylo can distinguish between Middle English dialects by using the less frequent character 3-grams.
Original language | English |
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Peer-reviewed scientific journal | Journal of Data Mining & Digital Humanities |
Volume | Special issue on Visualisations in Historical Linguistics |
Pages (from-to) | 1-10 |
Number of pages | 10 |
ISSN | 2416-5999 |
Publication status | Published - 23.12.2020 |
MoE publication type | A1 Journal article - refereed |
Keywords
- 612,1 Languages
- Middle English
- non-standard spelling
- historical dialectology
- diatopical variation
- unattended analysis
- stylometry
- authorship attribution
- R
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Dive into the research topics of 'Stylo visualisations of Middle English documents'. Together they form a unique fingerprint.Activities
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Journal of Data Mining & Digital Humanities (Journal)
Martti Mäkinen (Member of editorial board)
10.2018 → 31.12.2020Activity: Publication peer-review and editorial work › Special issue of journal
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20th International Conference on English Historical Linguistics
Martti Mäkinen (Speaker: Presenter)
27.08.2018 → 31.08.2018Activity: Participating in or organising an event › Organisation of / participation in conferences, workshops, courses, seminars
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