Exploring the Use of the Pronoun I in German Academic Texts with Machine Learning
Zusammenfassung
The use of the pronoun ich (‘I’) in academic language is a source of constant debate and a frequent cause of insecurity for students. We explore manually annotated instances of I from a German learner corpus. Using machine learning techniques, we investigate to what extent it is possible to automatically distinguish between different types of I usage (author I vs. narrator I). We additionally inspect which context words are good indicators of one type or the other. The results show that an automatic classification is not straightforward, but the distinctive features are in line with previous research. The results of the automatic classification are not perfect, but would greatly facilitate manual annotation. The distinctive words are in line with previous research and indicate that the author I is a more homogeneous class.
- Vollständige Referenz
- BibTeX
Andresen, M. & Knorr, D.,
(2021).
Exploring the Use of the Pronoun I in German Academic Texts with Machine Learning.
In:
Reussner, R. H., Koziolek, A. & Heinrich, R.
(Hrsg.),
INFORMATIK 2020.
Gesellschaft für Informatik, Bonn.
(S. 1327-1333).
DOI: 10.18420/inf2020_124
@inproceedings{mci/Andresen2021,
author = {Andresen, Melanie AND Knorr, Dagmar},
title = {Exploring the Use of the Pronoun I in German Academic Texts with Machine Learning},
booktitle = {INFORMATIK 2020},
year = {2021},
editor = {Reussner, Ralf H. AND Koziolek, Anne AND Heinrich, Robert} ,
pages = { 1327-1333 } ,
doi = { 10.18420/inf2020_124 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Andresen, Melanie AND Knorr, Dagmar},
title = {Exploring the Use of the Pronoun I in German Academic Texts with Machine Learning},
booktitle = {INFORMATIK 2020},
year = {2021},
editor = {Reussner, Ralf H. AND Koziolek, Anne AND Heinrich, Robert} ,
pages = { 1327-1333 } ,
doi = { 10.18420/inf2020_124 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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Mehr Information
DOI: 10.18420/inf2020_124
ISBN: 978-3-88579-701-2
ISSN: 1617-5468
Datum: 2021
Sprache:
(en)
(en)
