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Learner Corpus Anonymization in the Age of GDPR: Insights from the Creation of a Learner Corpus of Swedish
Stockholm University, Faculty of Humanities, Department of Swedish Language and Multilingualism, Scandinavian Languages.
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2018 (English)In: Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning at SLTC 2018 (NLP4CALL 2018), Linköping: Linköping University Electronic Press, 2018, p. 47-56, article id 006Conference paper, Published paper (Refereed)
Abstract [en]

This paper reports on the status of learner corpus anonymization for the ongoing research infrastructure project SweLL. The main project aim is to deliver and make available for research a well-annotated corpus of essays written by second language (L2) learners of Swedish. As the practice shows, annotation of learner texts is a sensitive process demanding a lot of compromises between ethical and legal demands on the one hand, and research and technical demands, on the other. Below, is a concise description of the current status of pseudonymization of language learner data to ensure anonymity of the learners, with numerous examples of the above-mentioned compromises.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 47-56, article id 006
Series
Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 152
National Category
General Language Studies and Linguistics Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:su:diva-162706ISBN: 978-91-7685-173-9 (print)OAI: oai:DiVA.org:su-162706DiVA, id: diva2:1269012
Conference
7th Workshop on NLP for Computer Assisted Language Learning at SLTC 2018 (NLP4CALL 2018), Stockholm, Sweden, 7th November, 2018
Funder
Riksbankens Jubileumsfond, IN16-0464:1Available from: 2018-12-07 Created: 2018-12-07 Last updated: 2019-03-11Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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