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Word embeddings quantify 100 years of gender and ethnic stereotypes
Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we develop a framework to demonstrate how the temporal...
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| Publicado en: | Proc Natl Acad Sci U S A |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
National Academy of Sciences
2018
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5910851/ https://ncbi.nlm.nih.gov/pubmed/29615513 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1720347115 |
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