Bambara Language Dataset for Sentiment Analysis
This addresses the problem of data scarcity for Bambara speakers and researchers, but it is incremental as it applies an existing method to new data.
The authors tackled the lack of datasets for underrepresented African languages by creating the first common-crawl-based Bambara dialectal dataset for sentiment analysis, making it freely available for NLP research.
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.