Wiktionary as a Crowdsourced Lexicon for English Dialects
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Abstract (arXiv)
This paper evaluates Wiktionary as an ethically crowdsourced lexicon for English dialects. We took a two-phase approach, providing an in-depth descriptive analysis of the crowdsourced lexicon for 12 national varieties of English before applying the lexicon to geo-referenced, country-level social media language data to examine the real-world performance of this crowdsourced dialect lexicon. We demonstrate that Wiktionary matches or exceeds the coverage of traditional dictionaries, such as the Oxford English Dictionary (OED), for regional and Outer-Circle varieties. Our dialect-specific case study on New Zealand English found high alignment between Wiktionary and the OED based on word-formation patterns (R = 0.883). Similarly, we observed high alignment between the dialect lexicon and geo-referenced social media language. While this paper found that Wiktionary has broad coverage of lexical properties, it also highlighted some of the macro-challenges involved in evaluating dialect-responsive language resources and tools, such as the role of language contact in dialects and register effects in web-based corpora.
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References · 9
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,360
- 2020The Pushshift Reddit Datasetcited by 291
- 2022Geographic and Geopolitical Biases of Language Modelscited by 29
- 2024Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Taskscited by 21
- 2025Do Large Language Models Understand Word Senses?cited by 10
- 2025Evaluation of LLMs in Medical Text Summarization: The Role of Vocabulary Adaptation in High OOV Settingscited by 4
- 2024Extracting Lexical Features from Dialects via Interpretable Dialect Classifierscited by 3
- 2026Language, Place, and Social Media: Geographic Dialect Alignment in New Zealandcited by 1
- 2026Lexicons and grammars for language processing: industrial or handcrafted products?cited by 1
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