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Cited by 499

The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.

The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings

Open access
Kozlowski, Austin C., Taddy, Matt, Evans, James A.·2019·American Sociological Review

Abstract

We argue word embedding models are a useful tool for the study of culture using a historical analysis of shared understandings of social class as an empirical case. Word embeddings represent semantic relations between words as relationships between vectors in a high-dimensional space, specifying a relational model of meaning consistent with contemporary theories of culture. Dimensions induced by word differences ( rich – poor) in these spaces correspond to dimensions of cultural meaning, and the projection of words onto these dimensions reflects widely shared associations, which we validate with surveys. Analyzing text from millions of books published over 100 years, we show that the markers of class continuously shifted amidst the economic transformations of the twentieth century, yet the basic cultural dimensions of class remained remarkably stable. The notable exception is education, which became tightly linked to affluence independent of its association with cultivated taste.

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Metadata

Authors
Kozlowski, A. C., Taddy, M., & Evans, J. A.
Venue
American Sociological Review
Published
2019-09-25
Volume
84
Issue
5
Pages
905-949
ISSN
  • 0003-1224 (ISSN-L)
  • 1939-8271
OpenAlex
W2794635328
Cited by
499
References
86
FWCI
79.77
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings. https://app.cochat.ai/papers/10.1177/0003122419877135
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Kozlowski, A. C., Taddy, M., & Evans, J. A. (2019). The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings. American Sociological Review. https://doi.org/10.1177/0003122419877135

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.