Beéta Megyesi
Uppsala University, Sweden
Lena Granstedt
Umeå University, Sweden
Sofia Johansson
Stockholm University, Sweden
Julia Prentice
University of Gothenburg, Sweden
Dan Rosén
University of Gothenburg, Sweden
Carl-Johan Schenström
University of Gothenburg, Sweden
Gunlög Sundberg
Stockholm University, Sweden
Mats Wirén
Stockholm University, Sweden
Elena Volodina
University of Gothenburg, Sweden
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Published in: Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018
Linköping Electronic Conference Proceedings 152:6, p. 47-56
NEALT Proceedings Series 36:6, p. 47-56
Published: 2018-11-02
ISBN: 978-91-7685-173-9
ISSN: 1650-3686 (print), 1650-3740 (online)
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.
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