Gender Bias Detection

We are working on studying methods to detect gendered language automatically using unsupervised learning methods, such as variational auto-encoders. The findings of our first paper on this (Hoyle et al., 2019) have been reported by 75+ international news outlets, including Forbes.

Currently, we’re interested in expanding the above to a cross-lingual study, as well as researching the relationship between gender bias and attitudes towards entities on social media as part of a project funded by DFF.

Publications

As NLP models are increasingly deployed in socially situated settings such as online abusive content detection, ensuring these models …

While the prevalence of large pre-trained language models has led to significant improvements in the performance of NLP systems, recent …

Machine Learning (ML) seeks to identify and encode bodies of knowledge within provided datasets. However, data encodes subjective …

Studying to what degree the language we use is gender-specific has long been an area of interest in socio-linguistics. Studies have …