5 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CL2022★ 1 cited
The effects of gender bias in word embeddings on depression prediction
Gizem Sogancioglu, Heysem Kaya
Word embeddings are extensively used in various NLP problems as a state-of-the-art semantic feature vector representation. Despite their success on various tasks and domains, they…
cs.CL2022★ 5 cited
Gender bias in (non)-contextual clinical word embeddings for stereotypical medical categories
Gizem Sogancioglu, Fabian Mijsters, Amar van Uden +1
Clinical word embeddings are extensively used in various Bio-NLP problems as a state-of-the-art feature vector representation. Although they are quite successful at the semantic re…
cs.CV2022★ 2 cited
Fact sheet: Automatic Self-Reported Personality Recognition Track
Francisca Pessanha, Gizem Sogancioglu
We propose an informed baseline to help disentangle the various contextual factors of influence in this type of case studies. For this purpose, we analysed the correlation between…