Racial Influence on Automated Perceptions of Emotions

By L. Rhue. 2018

131 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Sociology and Political Science, Sentiment & Opinion Analysis, AI Ethics, Fairness & Society

How researchers see this paper

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

In Experimental and Cognitive Psychology

1. Solon Barocas
2. Su Lin Blodgett
3. Li Fei-Fei

In Sociology and Political Science

1. Morgan Klaus Scheuerman
2. Jia Deng
3. Olga Russakovsky
4. Solon Barocas
5. Su Lin Blodgett
6. Angelina Wang
7. Li Fei-Fei

In Sentiment & Opinion Analysis

1. Klint Qinami
2. Jia Deng
3. Olga Russakovsky
4. Kaiyu Yang
5. Li Fei-Fei

In AI Ethics, Fairness & Society

1. Angelina Wang
2. Morgan Klaus Scheuerman
3. Olga Russakovsky
4. Solon Barocas
5. Su Lin Blodgett
6. Adrian Weller

Citations in the corpus

• Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy (2019, background): “In the context of computer vision, this issue has been brought up at least in face recognition [10], activity recognition [82], facial emotion recognition [62], face attribute detection [65] and image captioning [11] ś as well as more generally in pointing out the imaging bias of datasets [72].”
• Taxonomizing and Measuring Representational Harms: A Look at Image Tagging (2023, background): “…way to mitigate these stereotypes is to ensure that the distributions of tags for different social groups are similar—for example, that the distribution of tags applied to images of Black football players is similar to the distribution of tags applied to white football players (Rhue 2018).”