A Deep Learning Approach to Language-independent Gender Prediction on Twitter

By Reyhaneh Hashempour. 2019

4 citations recorded by the source corpus.

How researchers see this paper

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

1. Henrik Björklund
2. Hannah Devinney
3. Jenny Björklund

Citations in the corpus

• Queens Are Powerful Too: Mitigating Gender Bias in Dialogue Generation (2019, neutral): “…2019; Chang and McKeown 2019; Costa-juss ` a 2019; Du et al. 2019; Emami et al. 2019; Garimella et al. 2019; Gaut et al. 2020; Habash et al. 2019; Hashempour 2019; Hoyle et al. 2019; Lee et al. 2019a; Lepp 2019; Qian 2019; Qian et al. 2019; Sharifirad et al. 2019; Sharifirad and Matwin 2019;…”
• Theories of “Gender” in NLP Bias Research (2022, background): “52 [60] Reyhaneh Hashempour, Aline Villavicencio, Barbara Plank, and Renato Amorim.”