How Contentious Terms About People and Cultures are Used in Linked Open Data
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Abstract (arXiv)
Web resources in linked open data (LOD) are comprehensible to humans through literal textual values attached to them, such as labels, notes, or comments. Word choices in literals may not always be neutral. When outdated and culturally stereotyping terminology is used in literals, they may appear as offensive to users in interfaces and propagate stereotypes to algorithms trained on them. We study how frequently and in which literals contentious terms about people and cultures occur in LOD and whether there are attempts to mark the usage of such terms. For our analysis, we reuse English and Dutch terms from a knowledge graph that provides opinions of experts from the cultural heritage domain about terms' contentiousness. We inspect occurrences of these terms in four widely used datasets: Wikidata, The Getty Art & Architecture Thesaurus, Princeton WordNet, and Open Dutch WordNet. Some terms are ambiguous and contentious only in particular senses. Applying word sense disambiguation, we generate a set of literals relevant to our analysis. We found that outdated, derogatory, stereotyping terms frequently appear in descriptive and labelling literals, such as preferred labels that are usually displayed in interfaces and used for indexing. In some cases, LOD contributors mark contentious terms with words and phrases in literals (implicit markers) or properties linked to resources (explicit markers). However, such marking is rare and non-consistent in all datasets. Our quantitative and qualitative insights could be helpful in developing more systematic approaches to address the propagation of stereotypes via LOD.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 34 references that are in the map. First posted on arXiv 13 Nov 2023.
Builds on
5 of 34 references.
References · 5
- 2019A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?cited by 31
- 2019Falcon 2.0: An Entity and Relation Linking Tool over Wikidatacited by 21
- 2019Measuring Social Bias in Knowledge Graph Embeddingscited by 17
- 2022The Lifecycle of "Facts": A Survey of Social Bias in Knowledge Graphscited by 4
- 2018A Short Survey on Sense-Annotated Corporacited by 2
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Citing papers per year: 2024: 2.
2 papers.
- 2024A Survey on Lexical Ambiguity Detection and Word Sense Disambiguationcited by 5
- 2024Hybrid Intelligence for Digital Humanitiescited by 1
- 2024Hybrid Intelligence for Digital Humanities15 Apr 2024
- 2024A Survey on Lexical Ambiguity Detection and Word Sense Disambiguation24 Mar 2024