@inproceedings{kraft-usbeck-2022-lifecycle,
title = "The Lifecycle of {``}Facts{''}: A Survey of Social Bias in Knowledge Graphs",
author = "Kraft, Angelie and
Usbeck, Ricardo",
editor = "He, Yulan and
Ji, Heng and
Li, Sujian and
Liu, Yang and
Chang, Chua-Hui",
booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2022",
address = "Online only",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.aacl-main.49",
pages = "639--652",
abstract = "Knowledge graphs are increasingly used in a plethora of downstream tasks or in the augmentation of statistical models to improve factuality. However, social biases are engraved in these representations and propagate downstream. We conducted a critical analysis of literature concerning biases at different steps of a knowledge graph lifecycle. We investigated factors introducing bias, as well as the biases that are rendered by knowledge graphs and their embedded versions afterward. Limitations of existing measurement and mitigation strategies are discussed and paths forward are proposed.",
}
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%0 Conference Proceedings
%T The Lifecycle of “Facts”: A Survey of Social Bias in Knowledge Graphs
%A Kraft, Angelie
%A Usbeck, Ricardo
%Y He, Yulan
%Y Ji, Heng
%Y Li, Sujian
%Y Liu, Yang
%Y Chang, Chua-Hui
%S Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2022
%8 November
%I Association for Computational Linguistics
%C Online only
%F kraft-usbeck-2022-lifecycle
%X Knowledge graphs are increasingly used in a plethora of downstream tasks or in the augmentation of statistical models to improve factuality. However, social biases are engraved in these representations and propagate downstream. We conducted a critical analysis of literature concerning biases at different steps of a knowledge graph lifecycle. We investigated factors introducing bias, as well as the biases that are rendered by knowledge graphs and their embedded versions afterward. Limitations of existing measurement and mitigation strategies are discussed and paths forward are proposed.
%U https://aclanthology.org/2022.aacl-main.49
%P 639-652
Markdown (Informal)
[The Lifecycle of “Facts”: A Survey of Social Bias in Knowledge Graphs](https://aclanthology.org/2022.aacl-main.49) (Kraft & Usbeck, AACL-IJCNLP 2022)
ACL
- Angelie Kraft and Ricardo Usbeck. 2022. The Lifecycle of “Facts”: A Survey of Social Bias in Knowledge Graphs. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 639–652, Online only. Association for Computational Linguistics.