{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-geometry-of-culture-analyzing-meaning","title":"The Geometry of Culture: Analyzing Meaning through Word Embeddings","arxiv_id":"1803.09288","date":"2018-03-25","proceeding":null,"authors":["Austin C. Kozlowski","Matt Taddy","James A. Evans"],"abstract":"We demonstrate the utility of a new methodological tool, neural-network word\nembedding models, for large-scale text analysis, revealing how these models\nproduce richer insights into cultural associations and categories than possible\nwith prior methods. Word embeddings represent semantic relations between words\nas geometric relationships between vectors in a high-dimensional space,\noperationalizing a relational model of meaning consistent with contemporary\ntheories of identity and culture. We show that dimensions induced by word\ndifferences (e.g. man - woman, rich - poor, black - white, liberal -\nconservative) in these vector spaces closely correspond to dimensions of\ncultural meaning, and the projection of words onto these dimensions reflects\nwidely shared cultural connotations when compared to surveyed responses and\nlabeled historical data. We pilot a method for testing the stability of these\nassociations, then demonstrate applications of word embeddings for\nmacro-cultural investigation with a longitudinal analysis of the coevolution of\ngender and class associations in the United States over the 20th century and a\ncomparative analysis of historic distinctions between markers of gender and\nclass in the U.S. and Britain. We argue that the success of these\nhigh-dimensional models motivates a move towards \"high-dimensional theorizing\"\nof meanings, identities and cultural processes.","url_abs":"http://arxiv.org/abs/1803.09288v1","url_pdf":"http://arxiv.org/pdf/1803.09288v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-geometry-of-culture-analyzing-meaning","repo_url":"https://github.com/UC-MACSS/persp-analysis_A18","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"culture","task_name":"Cultural Vocal Bursts Intensity Prediction"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1803.09288","atlas_url":"https://app.syntology.ai/?focus=1803.09288","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}