mlsanityData to 14 Oct 2026

Assessing Digital Language Support on a Global Scale

arXiv 2209.13515 ↗First posted 27 Sep 2022cs.CLcited by 6

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Abstract (arXiv)

The users of endangered languages struggle to thrive in a digitally-mediated world. We have developed an automated method for assessing how well every language recognized by ISO 639 is faring in terms of digital language support. The assessment is based on scraping the names of supported languages from the websites of 143 digital tools selected to represent a full range of ways that digital technology can support languages. The method uses Mokken scale analysis to produce an explainable model for quantifying digital language support and monitoring it on a global scale.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 4 of its 36 references that are in the map. First posted on arXiv 27 Sep 2022.

Builds on

4 of 36 references.

References · 4

  1. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,206
  2. 2021Systematic Inequalities in Language Technology Performance across the World's Languagescited by 120
  3. 2022Building Machine Translation Systems for the Next Thousand Languagescited by 69
  4. 2019Unsung Challenges of Building and Deploying Language Technologies for Low Resource Language Communitiescited by 19

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 2.

6 papers.

  1. 2024The Zeno's Paradox of `Low-Resource' Languagescited by 12
  2. 2023The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generationcited by 11
  3. 2025Invisible Languages of the LLM Universecited by 4
  4. 2023CebuaNER: A New Baseline Cebuano Named Entity Recognition Modelcited by 2
  5. 2026M-GATE: Multilingual Grammar, Accuracy in Translation, and Efficiency Benchmark for Large Language Modelscited by 1
  6. 2026UzWordnet and Generative AI for Learning Uzbek by Game Playingcited by 0