Measuring gender stereotype reinforcement in information retrieval systems
Contributo in Atti di convegno
Data di Pubblicazione:
2021
Abstract:
Can we measure the tendency of an Information Retrieval (IR) system to reinforce gender stereotypes in its users? In this abstract, we define the construct of Gender Stereotype Reinforcement (GSR) in the context of IR and propose a measure for it based on Word Embeddings. We briefly discuss the validity of our measure and summarize our experiments on different families of IR systems.
Tipologia CRIS:
04.01 - Contributo in atti di convegno
Keywords:
Fairness; Gender stereotypes; Information retrieval; Search engines; Word embeddings
Elenco autori:
Fabris, A.; Purpura, A.; Silvello, G.; Susto, G. A.
Link alla scheda completa:
Titolo del libro:
CEUR Workshop Proceedings
Pubblicato in: