ReviewThe British journal of social psychology2023
Using word embeddings to investigate cultural biases.
Review in The British journal of social psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- Anchoring race: improving the construction of race dimensions in word embeddings.Journal of computational social science · 2026Article
- Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese.Frontiers in neuroscience · 2025Article
- The news in black and white: word embeddings quantify racism in South African news.EPJ data science · 2025Article
- Whose voice matters? Word embeddings reveal identity bias in news quotes.EPJ data science · 2025Article
- Article
- Article
- Emotion topology: extracting fundamental components of emotions from text using word embeddings.Frontiers in psychology · 2024Article
- Word embedding for social sciences: an interdisciplinary survey.PeerJ. Computer science · 2024Review
- Using word embeddings to investigate cultural biases.The British journal of social psychology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Word embeddings provide quantitative representations of word semantics and the associations between word meanings in text data, including in large repositories in media and social media archives. This article introduces social psychologists to word embedding research via a consideration of bias analysis, a topic of central concern in the discipline. We explain how word embeddings are constructed and how they can be used to measure bias along bipolar dimensions that are comparable to semantic differential scales. We review recent studies that show how familiar social biases can be detected in embeddings and how these change over time and in conjunction with real-world discriminatory practices. The evidence suggests that embeddings yield valid and reliable estimates of bias and that they can identify subtle biases that may not be communicated explicitly. We argue that word embedding research can extend scholarship on prejudice and stereotyping, providing measures of the bias environment of human thought and action.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.