Gender Classification for Podcast Media – EPFL Capstone Project for COS Applied Data Science: Machine Learning

Code for measuring gender bias in word embeddings

NamSor API v2 Java SDK - classify personal names accurately by gender, country of origin, or ethnicity.

Pruning bias from transformers / NAACL 2022

This repository contains the required codes for reproducing the results in "Gender Bias in Legal Texts and Debiasing It" which is published in Natural Language Engineering journal.

Topic Modeling for Gender Bias on Regional News Corpus

Interpseech 2024 - News Topic classification (dataset, evaluation and models source)

Code for the paper "Challenges in Measuring Bias in Open-Ended Language Generation" presented as oral at the 4th Workshop on Gender Bias in NLP at NAACL 2022.

This repository contains an exploratory data analysis project focused on investigating gender bias in Spanish films through the lens of the Bechdel Test. The Bechdel Test, originating from Alison Bechdel, is a measure of representation of women in fiction, setting a low bar for gender equality in storytelling.

Code/Data for the paper: "Auditing Gender Presentation Differences in Text-to-Image Models"

A reply to BMJ 2019;367:l6573

Reproduction Attempt for "Gender Bias among Professionals"

Code and data for the paper "An Information-Theoretic Approach and Dataset for Probing Gender Stereotypes in Multilingual Masked Language Models" (Findings of NAACL 2022)

The project can be split into different sub-projects (easy difficulty: replication of the published meta-analysis for evidence of gender bias in hiring decisions; medium for newer modelling). Requires skills in R and will require some learning on Bayesian modelling.

To understand the gender/social bias Bert KD model, more specifically TinyBert.

Gender Bias Detection on Websites using AI

Visualize interactions between different genders in any given text.

Literature overview: gender bias in natural language processing

Son Bias in US: Evidence from Business Names

Analysis and visualization of the gender wage gap dataset from OECD using MySQL, the PyMySQL and Pandas modules from Python, and Jupyter Notebook.