Whose voice matters? Word embeddings reveal identity bias in news quotes

Authors

Institutions

Publication Details

Journal
EPJ Data Science
Published
2025-04-17
DOI
https://doi.org/10.1140/epjds/s13688-025-00541-1
Citations
1
Primary Topic
Discourse Analysis in Language Studies
Type
article
Field-Weighted Citation Impact
15.18

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Whose voice matters? Word embeddings reveal identity bias in news quotes

Mpho Primus, Kevin Durrheim, Nnaemeka Ohamadike
1 citations
EPJ Data Science
Discourse Analysis in Language Studies
15.18
article

Whose voice matters? Word embeddings reveal identity bias in news quotes

Mpho Primus, Kevin Durrheim, Nnaemeka Ohamadike
article en
1 citations

Abstract

No abstract available for this paper.
EPJ Data ScienceVol. 14(1)
University of Johannesburg (ZA)
National Science Foundation, National Research Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, University of Johannesburg
Gender equality
Openalex Percentile: Top 3%
Discourse Analysis in Language Studies
15.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Whose voice matters? Word embeddings reveal identity bias in news quotes — Mpho Primus, Kevin Durrheim, et al. · EPJ Data Science (2025) | TGRS Research Map | TGRS