Measuring Gender Bias in News Images

By Sen Jia, Thomas Lansdall-Welfare, Nello Cristianini. 2015

19 citations recorded by the source corpus.

Subfields: Communication, Gender Studies, Sociology and Political Science, Safety, Robustness & Interpretability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Gender Studies

1. C. Knight

In Sociology and Political Science

1. Stan Oklobdzija
2. Emily Bello-Pardo
3. Nello Cristianini
4. Jeffrey W. Lockhart
5. C. Knight
6. Martijn Schoonvelde
7. Carsten Schwemmer

In Safety, Robustness & Interpretability

1. Stan Oklobdzija
2. Thomas Lansdall-Welfare
3. Emily Bello-Pardo
4. Nello Cristianini
5. Sen Jia
6. Jeffrey W. Lockhart
7. C. Knight
8. Martijn Schoonvelde

Citations in the corpus

• Diagnosing Gender Bias in Image Recognition Systems (2020, background): “The political realm has consistently revealed gender bias in the representation of women in images (Jia et al. 2015).”
• Gender Classification by Deep Learning on Millions of Weakly Labelled Images (2016, background): “Applications are readily found in many areas, for example in the analysis of gender bias in news media content [1], [2].”