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  Uncovering the language of wine experts

Croijmans, I., Hendrickx, I., Lefever, E., Majid, A., & Van den Bosch, A. (2020). Uncovering the language of wine experts. Natural Language Engineering, 26(5), 511-530. doi:10.1017/S1351324919000500.

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Croijmans_etal_2020_Uncovering the language of wine experts.pdf (Verlagsversion), 3MB
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2019
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© Cambridge University Press 2019 This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial licence (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited

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 Urheber:
Croijmans, Ilja1, 2, Autor           
Hendrickx, Iris1, Autor
Lefever, Els3, Autor
Majid, Asifa1, 4, 5, 6, Autor           
Van den Bosch, Antal1, 7, Autor
Affiliations:
1Center for Language Studies , External Organizations, ou_55238              
2Utrecht University, Utrecht, The Netherlands, ou_persistent22              
3Ghent University, Ghent, Belgium, ou_persistent22              
4Donders Institute for Brain, Cognition and Behaviour, External Organizations, ou_55236              
5Other Research, MPI for Psycholinguistics, Max Planck Society, Nijmegen, NL, ou_55217              
6University of York, Heslington, UK, ou_persistent22              
7Meertens Institute, Amsterdam, The Netherlands, ou_persistent22              

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 Zusammenfassung: Talking about odors and flavors is difficult for most people, yet experts appear to be able to convey critical information about wines in their reviews. This seems to be a contradiction, and wine expert descriptions are frequently received with criticism. Here, we propose a method for probing the language of wine reviews, and thus offer a means to enhance current vocabularies, and as a by-product question the general assumption that wine reviews are gibberish. By means of two different quantitative analyses—support vector machines for classification and Termhood analysis—on a corpus of online wine reviews, we tested whether wine reviews are written in a consistent manner, and thus may be considered informative; and whether reviews feature domain-specific language. First, a classification paradigm was trained on wine reviews from one set of authors for which the color, grape variety, and origin of a wine were known, and subsequently tested on data from a new author. This analysis revealed that, regardless of individual differences in vocabulary preferences, color and grape variety were predicted with high accuracy. Second, using Termhood as a measure of how words are used in wine reviews in a domain-specific manner compared to other genres in English, a list of 146 wine-specific terms was uncovered. These words were compared to existing lists of wine vocabulary that are currently used to train experts. Some overlap was observed, but there were also gaps revealed in the extant lists, suggesting these lists could be improved by our automatic analysis.

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Sprache(n): eng - English
 Datum: 2020-08
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1017/S1351324919000500
 Art des Abschluß: -

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Titel: Natural Language Engineering
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Cambridge, UK : Cambridge University Press
Seiten: - Band / Heft: 26 (5) Artikelnummer: - Start- / Endseite: 511 - 530 Identifikator: ISSN: 1351-3249
CoNE: https://pure.mpg.de/cone/journals/resource/954925342769