Built on

Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them
Original
Hila Gonen and Yoav Goldberg. 2019 · 1903
Earlier work this paper cites.
On measuring social biases in sentence encoders
Original
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019 · 1903
Earlier work this paper cites.
Evaluating the underlying gender bias in contextualized word embeddings
Original
Christine Basta, Marta Ruiz Costa-jussà, and Noe Casas. 2019 · 1904
Earlier work this paper cites.
Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings
Original
Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov, and Alan W Black. 2019 · 1904
Earlier work this paper cites.
Compositional fairness constraints for graph embeddings
Original
Avishek Joey Bose and William Hamilton. 2019 · 1905
Earlier work this paper cites.
Fair is better than sensational: Man is to doctor as woman is to doctor
Original
Malvina Nissim, Rik van Noord, and Rob van der Goot. 2019 · 1905
Earlier work this paper cites.
ERNIE: enhanced language representation with informative entities
Original
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 1905
Earlier work this paper cites.
Barack’s wife hillary: Using knowledge-graphs for fact-aware language modeling
Original
Robert L. Logan IV, Nelson F. Liu, Matthew E. Peters, Matt Gardner, and Sameer Singh. 2019 · 1906
Earlier work this paper cites.
Evaluating gender bias in machine translation
Original
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019 · 1906
Earlier work this paper cites.

Similar

Measuring sex stereotypes: A multination study, rev. ed
J. E. Hall Williams and Deborah L. Best. 1990 · 1990
Cited alongside, same era.
Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
Cited alongside, same era.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Durán, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Cited alongside, same era.
Uneven geographies of user-generated information: Patterns of increasing informational poverty
Mark Graham, Bernie Hogan, Ralph K. Straumann, and Ahmed Medhat. 2014 · 2014
Cited alongside, same era.
It’s a man’s wikipedia? assessing gender inequality in an online encyclopedia
Original
Claudia Wagner, David García, Mohsen Jadidi, and Markus Strohmaier. 2015 · 2015
Cited alongside, same era.

Then

Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna Bryson, and Arvind Narayanan. 2017 · 2017
Later among the works it cites.
Word embeddings quantify 100 years of gender and ethnic stereotypes
Original
Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou. 2017 · 2017
Later among the works it cites.
Gender bias in coreference resolution
Original
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
Later among the works it cites.
Ai can be sexist and racist—it’s time to make it fair
James Zou and Londa Schiebinger. 2018 · 2018
Later among the works it cites.
Machine learning and bias
Tim Jones. 2019 · 2019
Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Reading the bibliography…

2019

Measuring Social Bias in Knowledge Graph Embeddings

Fisher, Joseph, Palfrey, Dave, Christodoulopoulos, Christos et al.

Understand

It has recently been shown that word embeddings encode social biases, with a harmful impact on downstream tasks.

However, to this point there has been no similar work done in the field of graph embeddings.
We present the first study on social bias in knowledge graph embeddings, and propose a new metric suitable for measuring such bias.
We conduct experiments on Wikidata and Freebase, and show that, as with word embeddings, harmful social biases related to professions are encoded in the embeddings with respect to gender, religion, ethnicity and nationality.

Built on

Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them
Original
Hila Gonen and Yoav Goldberg. 2019 · 1903
Earlier work this paper cites.
On measuring social biases in sentence encoders
Original
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019 · 1903
Earlier work this paper cites.
Evaluating the underlying gender bias in contextualized word embeddings
Original
Christine Basta, Marta Ruiz Costa-jussà, and Noe Casas. 2019 · 1904
Earlier work this paper cites.
Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings
Original
Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov, and Alan W Black. 2019 · 1904
Earlier work this paper cites.
Compositional fairness constraints for graph embeddings
Original
Avishek Joey Bose and William Hamilton. 2019 · 1905
Earlier work this paper cites.
Fair is better than sensational: Man is to doctor as woman is to doctor
Original
Malvina Nissim, Rik van Noord, and Rob van der Goot. 2019 · 1905
Earlier work this paper cites.
ERNIE: enhanced language representation with informative entities
Original
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 1905
Earlier work this paper cites.
Barack’s wife hillary: Using knowledge-graphs for fact-aware language modeling
Original
Robert L. Logan IV, Nelson F. Liu, Matthew E. Peters, Matt Gardner, and Sameer Singh. 2019 · 1906
Earlier work this paper cites.
Evaluating gender bias in machine translation
Original
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019 · 1906
Earlier work this paper cites.

Similar

Measuring sex stereotypes: A multination study, rev. ed
J. E. Hall Williams and Deborah L. Best. 1990 · 1990
Cited alongside, same era.
Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
Cited alongside, same era.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Durán, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Cited alongside, same era.
Uneven geographies of user-generated information: Patterns of increasing informational poverty
Mark Graham, Bernie Hogan, Ralph K. Straumann, and Ahmed Medhat. 2014 · 2014
Cited alongside, same era.
It’s a man’s wikipedia? assessing gender inequality in an online encyclopedia
Original
Claudia Wagner, David García, Mohsen Jadidi, and Markus Strohmaier. 2015 · 2015
Cited alongside, same era.

Then

Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna Bryson, and Arvind Narayanan. 2017 · 2017
Later among the works it cites.
Word embeddings quantify 100 years of gender and ethnic stereotypes
Original
Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou. 2017 · 2017
Later among the works it cites.
Gender bias in coreference resolution
Original
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
Later among the works it cites.
Ai can be sexist and racist—it’s time to make it fair
James Zou and Londa Schiebinger. 2018 · 2018
Later among the works it cites.
Machine learning and bias
Tim Jones. 2019 · 2019
Closest in time.