The TRANSCOMP Dataset of Literary Translations from 120 Languages and a Parallel Collection of English-language Originals. (26th December 2022)
- Record Type:
- Journal Article
- Title:
- The TRANSCOMP Dataset of Literary Translations from 120 Languages and a Parallel Collection of English-language Originals. (26th December 2022)
- Main Title:
- The TRANSCOMP Dataset of Literary Translations from 120 Languages and a Parallel Collection of English-language Originals
- Authors:
- Erlin, Matt
Piper, Andrew
Knox, Douglas
Pentecost, Stephen
Blank, Allie - Abstract:
- The TRANSCOMP Dataset of Literary Translations is a collection of document-level word frequencies sampled from 10, 631 translations into English of global literary fiction published since 1950, together with a historically matched parallel corpus of 10, 682 fictional works originally published in English. We provide CSV files with word frequency counts for 10, 000-word samples taken from each text. The associated metadata is available in a separate CSV. These data will be useful to literary scholars and linguists working in translation studies, and those interested in the linguistic, stylistic, and thematic specificity of translations from particular regions.
- Is Part Of:
- Journal of open humanities data. Volume 8(2022)
- Journal:
- Journal of open humanities data
- Issue:
- Volume 8(2022)
- Issue Display:
- Volume 8, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 8
- Issue:
- 2022
- Issue Sort Value:
- 2022-0008-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12-26
- Subjects:
- translation studies -- computational literary studies -- world literature -- natural language processing -- text corpus -- text collection
Humanities -- Periodicals
001.3 - Journal URLs:
- http://openhumanitiesdata.metajnl.com/ ↗
- DOI:
- 10.5334/johd.94 ↗
- Languages:
- English
- ISSNs:
- 2059-481X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 25225.xml