# Bambara Language Dataset for Sentiment Analysis

arXiv: https://arxiv.org/abs/2108.02524 · HTML: https://mlsanity.com/paper/2108.02524/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 4 references that are in the map.
- First posted on arXiv 5 Aug 2021.

## Builds on (most cited first, 1 of 1)

- [Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara](https://mlsanity.com/paper/2011.05284/) (2020)

## Built on by (most cited first, 4 of 4)

- [SERENGETI: Massively Multilingual Language Models for Africa](https://mlsanity.com/paper/2212.10785/) (2022)
- [Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead](https://mlsanity.com/paper/2505.21315/) (2025)
- [State of NLP in Kenya: A Survey](https://mlsanity.com/paper/2410.09948/) (2024)
- [UBC-DLNLP at SemEval-2023 Task 12: Impact of Transfer Learning on African Sentiment Analysis](https://mlsanity.com/paper/2304.11256/) (2023)

## Abstract (arXiv)

For easier communication, posting, or commenting on each others posts, people use their dialects. In Africa, various languages and dialects exist. However, they are still underrepresented and not fully exploited for analytical studies and research purposes. In order to perform approaches like Machine Learning and Deep Learning, datasets are required. One of the African languages is Bambara, used by citizens in different countries. However, no previous work on datasets for this language was performed for Sentiment Analysis. In this paper, we present the first common-crawl-based Bambara dialectal dataset dedicated for Sentiment Analysis, available freely for Natural Language Processing research purposes.