Uncovering the language of wine experts Article Swipe
Ilja Croijmans
,
Iris Hendrickx
,
Els Lefever
,
Asifa Majid
,
Antal van den Bosch
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1017/s1351324919000500
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1017/s1351324919000500
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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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1017/s1351324919000500
- https://www.cambridge.org/core/services/aop-cambridge-core/content/view/9BF0A599B49230297FD6DBA01F07C0DD/S1351324919000500a.pdf/div-class-title-uncovering-the-language-of-wine-experts-div.pdf
- OA Status
- bronze
- Cited By
- 38
- References
- 103
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2975743152
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2975743152Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1017/s1351324919000500Digital Object Identifier
- Title
-
Uncovering the language of wine expertsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-09-23Full publication date if available
- Authors
-
Ilja Croijmans, Iris Hendrickx, Els Lefever, Asifa Majid, Antal van den BoschList of authors in order
- Landing page
-
https://doi.org/10.1017/s1351324919000500Publisher landing page
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/9BF0A599B49230297FD6DBA01F07C0DD/S1351324919000500a.pdf/div-class-title-uncovering-the-language-of-wine-experts-div.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
- OA URL
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/9BF0A599B49230297FD6DBA01F07C0DD/S1351324919000500a.pdf/div-class-title-uncovering-the-language-of-wine-experts-div.pdfDirect OA link when available
- Concepts
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Wine, Computer science, Variety (cybernetics), Natural language processing, Set (abstract data type), Artificial intelligence, Vocabulary, Feature (linguistics), Domain (mathematical analysis), Information retrieval, Linguistics, Mathematics, Programming language, Mathematical analysis, Philosophy, Optics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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38Total citation count in OpenAlex
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2025: 4, 2024: 5, 2023: 10, 2022: 8, 2021: 7Per-year citation counts (last 5 years)
- References (count)
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103Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.criticism. | 40 |
| abstract_inverted_index.frequently | 37 |
| abstract_inverted_index.gibberish. | 74 |
| abstract_inverted_index.individual | 160 |
| abstract_inverted_index.regardless | 158 |
| abstract_inverted_index.suggesting | 237 |
| abstract_inverted_index.uncovered. | 205 |
| abstract_inverted_index.vocabulary | 163, 215 |
| abstract_inverted_index.differences | 161 |
| abstract_inverted_index.information | 20 |
| abstract_inverted_index.descriptions | 35 |
| abstract_inverted_index.informative; | 111 |
| abstract_inverted_index.preferences, | 164 |
| abstract_inverted_index.quantitative | 80 |
| abstract_inverted_index.subsequently | 146 |
| abstract_inverted_index.analysis—on | 88 |
| abstract_inverted_index.vocabularies, | 61 |
| abstract_inverted_index.wine-specific | 202 |
| abstract_inverted_index.classification | 85, 120 |
| abstract_inverted_index.contradiction, | 31 |
| abstract_inverted_index.domain-specific | 116, 190 |
| abstract_inverted_index.analyses—support | 81 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 97 |
| corresponding_author_ids | https://openalex.org/A5004762264 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I145872427, https://openalex.org/I193662353 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.6600000262260437 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.97042366 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |