The Lifecycle of Facts: On Social Biases in Knowledge Graphs

Published in Proc. AACL-IJCNLP, 2022

Recommended citation: Kraft, A. and Usbeck, R. (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, pages 639–652, Online only. Association for Computational Linguistics. https://aclanthology.org/2022.aacl-main.49/

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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