Papers by Daphna Keidar

2 papers
Towards Automatic Bias Detection in Knowledge Graphs (2021.findings-emnlp)

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Challenge: Recent studies have shown that knowledge graphs are prone to various social biases, and have proposed multiple methods for debiasing them.
Approach: They propose a framework for identifying biases present in knowledge graph embeddings based on numerical bias metrics.
Outcome: The proposed framework can be extended to further bias definitions and applications.
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang (2022.acl-long)

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Challenge: a recent study suggests that language evolution is a diachronic process, but no causal analysis is performed to verify these claims.
Approach: They analyze the semantic change and frequency shift of slang words and compare them to those of standard, nonslang terms.
Outcome: The proposed model shows that slang has smaller semantic change but larger frequency shifts over time.

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