Palimpsest: improving assisted curation of loco-specific literature

Text mining and information visualization techniques applied to large-scale historical and literary document collections have enabled new types of humanities research. The assumption behind such efforts is often that trends will emerge from the analysis despite errors for individual data points and...

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Main Authors: Alex, Beatrice, Grover, Claire, Oberlander, Jon, Thomson, Tara, Anderson, Miranda, Loxley, James, Hinrichs, Uta, Zhou, Ke
Format: Article
Published: Oxford University Press 2017
Online Access:https://eprints.nottingham.ac.uk/46920/
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author Alex, Beatrice
Grover, Claire
Oberlander, Jon
Thomson, Tara
Anderson, Miranda
Loxley, James
Hinrichs, Uta
Zhou, Ke
author_facet Alex, Beatrice
Grover, Claire
Oberlander, Jon
Thomson, Tara
Anderson, Miranda
Loxley, James
Hinrichs, Uta
Zhou, Ke
author_sort Alex, Beatrice
building Nottingham Research Data Repository
collection Online Access
description Text mining and information visualization techniques applied to large-scale historical and literary document collections have enabled new types of humanities research. The assumption behind such efforts is often that trends will emerge from the analysis despite errors for individual data points and that noise will be dominated by the signal in the data. However, for some text analysis tasks, the technology is unable to perform as well as domain experts, perhaps because it does not have sufficient world knowledge or metadata available. Yet, the advantage of language processing technology is that it can process at scale, even if not perfectly accurately. Geo-locating literary works is one example where human expert knowledge is invaluable when it comes to distinguishing between candidate works. This was the underlying assumption in Palimpsest, an interdisciplinary digital humanities research project on mining literary Edinburgh. From the outset, the project adopted an assisted curation process whereby the automatic processing of large data collections was combined with manual checking to identify literary works set in Edinburgh. In this article, we introduce the assisted curation process and evaluate how the feedback from literary scholars helped to improve the technology, thereby highlighting the importance of placing humanities research at the core of digital humanities projects.
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spelling nottingham-469202020-05-04T19:57:52Z https://eprints.nottingham.ac.uk/46920/ Palimpsest: improving assisted curation of loco-specific literature Alex, Beatrice Grover, Claire Oberlander, Jon Thomson, Tara Anderson, Miranda Loxley, James Hinrichs, Uta Zhou, Ke Text mining and information visualization techniques applied to large-scale historical and literary document collections have enabled new types of humanities research. The assumption behind such efforts is often that trends will emerge from the analysis despite errors for individual data points and that noise will be dominated by the signal in the data. However, for some text analysis tasks, the technology is unable to perform as well as domain experts, perhaps because it does not have sufficient world knowledge or metadata available. Yet, the advantage of language processing technology is that it can process at scale, even if not perfectly accurately. Geo-locating literary works is one example where human expert knowledge is invaluable when it comes to distinguishing between candidate works. This was the underlying assumption in Palimpsest, an interdisciplinary digital humanities research project on mining literary Edinburgh. From the outset, the project adopted an assisted curation process whereby the automatic processing of large data collections was combined with manual checking to identify literary works set in Edinburgh. In this article, we introduce the assisted curation process and evaluate how the feedback from literary scholars helped to improve the technology, thereby highlighting the importance of placing humanities research at the core of digital humanities projects. Oxford University Press 2017-04 Article PeerReviewed Alex, Beatrice, Grover, Claire, Oberlander, Jon, Thomson, Tara, Anderson, Miranda, Loxley, James, Hinrichs, Uta and Zhou, Ke (2017) Palimpsest: improving assisted curation of loco-specific literature. Digital Scholarship in the Humanities, 32 (Supp 1). i4-i16. ISSN 2055-768X https://academic.oup.com/dsh/article-lookup/doi/10.1093/llc/fqw050#88522354 doi:10.1093/llc/fqw050 doi:10.1093/llc/fqw050
spellingShingle Alex, Beatrice
Grover, Claire
Oberlander, Jon
Thomson, Tara
Anderson, Miranda
Loxley, James
Hinrichs, Uta
Zhou, Ke
Palimpsest: improving assisted curation of loco-specific literature
title Palimpsest: improving assisted curation of loco-specific literature
title_full Palimpsest: improving assisted curation of loco-specific literature
title_fullStr Palimpsest: improving assisted curation of loco-specific literature
title_full_unstemmed Palimpsest: improving assisted curation of loco-specific literature
title_short Palimpsest: improving assisted curation of loco-specific literature
title_sort palimpsest: improving assisted curation of loco-specific literature
url https://eprints.nottingham.ac.uk/46920/
https://eprints.nottingham.ac.uk/46920/
https://eprints.nottingham.ac.uk/46920/