Low-resourced Languages and Online Knowledge Repositories: A Need-Finding Study
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Abstract (arXiv)
Online Knowledge Repositories (OKRs) like Wikipedia offer communities a way to share and preserve information about themselves and their ways of living. However, for communities with low-resourced languages -- including most African communities -- the quality and volume of content available are often inadequate. One reason for this lack of adequate content could be that many OKRs embody Western ways of knowledge preservation and sharing, requiring many low-resourced language communities to adapt to new interactions. To understand the challenges faced by low-resourced language contributors on the popular OKR Wikipedia, we conducted (1) a thematic analysis of Wikipedia forum discussions and (2) a contextual inquiry study with 14 novice contributors. We focused on three Ethiopian languages: Afan Oromo, Amharic, and Tigrinya. Our analysis revealed several recurring themes; for example, contributors struggle to find resources to corroborate their articles in low-resourced languages, and language technology support, like translation systems and spellcheck, result in several errors that waste contributors' time. We hope our study will support designers in making online knowledge repositories accessible to low-resourced language speakers.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 97 references that are in the map. First posted on arXiv 26 May 2024.
Builds on
10 of 97 references.
References · 10
- 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,290
- 2021Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpuscited by 481
- 2020Participatory Research for Low-resourced Machine Translation: A Case Study in African Languagescited by 159
- 2021AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processingcited by 131
- 2020Mitigating Gender Bias in Machine Translation with Target Gender Annotationscited by 42
- 2023WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?cited by 28
- 2021Narratives and Counternarratives on Data Sharing in Africacited by 14
- 2022When Is TTS Augmentation Through a Pivot Language Useful?cited by 7
- 2021Lesan -- Machine Translation for Low Resource Languagescited by 5
- 2016Growing Wikipedia Across Languages via Recommendationcited by 3
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editionscited by 3
- 2026Lost in Transcription: How Speech-to-Text Errors Derail Code Understandingcited by 1
- 2025CodeVaani: A Multilingual, Voice-Based Code Learning Assistantcited by 0
- 2026L-ReLF: A Framework for Lexical Dataset Creationcited by 0
- 2026Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Educationcited by 0
- 2026Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education8 Apr 2026
- 2026L-ReLF: A Framework for Lexical Dataset Creation31 Mar 2026
- 2026Lost in Transcription: How Speech-to-Text Errors Derail Code Understanding20 Jan 2026
- 2025CodeVaani: A Multilingual, Voice-Based Code Learning Assistant8 Oct 2025
- 2025WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editions30 May 2025