# Low-resourced Languages and Online Knowledge Repositories: A Need-Finding Study

arXiv: https://arxiv.org/abs/2405.16669 · HTML: https://mlsanity.com/paper/2405.16669/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 97 references that are in the map.
- First posted on arXiv 26 May 2024.

## Builds on (most cited first, 10 of 10)

- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)
- [Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus](https://mlsanity.com/paper/2104.08758/) (2021)
- [Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages](https://mlsanity.com/paper/2010.02353/) (2020)
- [AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing](https://mlsanity.com/paper/2108.05542/) (2021)
- [Mitigating Gender Bias in Machine Translation with Target Gender Annotations](https://mlsanity.com/paper/2010.06203/) (2020)
- [WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?](https://mlsanity.com/paper/2305.06415/) (2023)
- [Narratives and Counternarratives on Data Sharing in Africa](https://mlsanity.com/paper/2103.01168/) (2021)
- [When Is TTS Augmentation Through a Pivot Language Useful?](https://mlsanity.com/paper/2207.09889/) (2022)
- [Lesan -- Machine Translation for Low Resource Languages](https://mlsanity.com/paper/2112.08191/) (2021)
- [Growing Wikipedia Across Languages via Recommendation](https://mlsanity.com/paper/1604.03235/) (2016)

## Built on by (most cited first, 5 of 5)

- [WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editions](https://mlsanity.com/paper/2505.24195/) (2025)
- [Lost in Transcription: How Speech-to-Text Errors Derail Code Understanding](https://mlsanity.com/paper/2601.15339/) (2026)
- [CodeVaani: A Multilingual, Voice-Based Code Learning Assistant](https://mlsanity.com/paper/2511.20654/) (2025)
- [L-ReLF: A Framework for Lexical Dataset Creation](https://mlsanity.com/paper/2603.29346/) (2026)
- [Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education](https://mlsanity.com/paper/2604.07253/) (2026)

## 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.