2021/08/05 by Mountaga Diallo, Diallo, Mountaga, Chayma Fourati +3 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2108.02524
openalex publication_date 2021/08/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.