| dataset_info: | |
| features: | |
| - name: text | |
| dtype: string | |
| - name: label | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 120478 | |
| num_examples: 1001 | |
| download_size: 65426 | |
| dataset_size: 120478 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: apache-2.0 | |
| task_categories: | |
| - text-classification | |
| language: | |
| - kg | |
| ## Dataset Summary | |
| AfriSenti is the largest sentiment analysis dataset for under-represented African languages, covering 110,000+ annotated tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba). | |
| The datasets are used in the first Afrocentric SemEval shared task, SemEval 2023 Task 12: Sentiment analysis for African languages (AfriSenti-SemEval). AfriSenti allows the research community to build sentiment analysis systems for various African languages and enables the study of sentiment and contemporary language use in African languages. |