Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Karagas
Size:
10K - 100K
License:
| license: mit | |
| task_categories: | |
| - text-classification | |
| language: | |
| - kim | |
| tags: | |
| - sentiment | |
| - african-languages | |
| - nlp | |
| - text-classification | |
| - binary-classification | |
| size_categories: | |
| - 10K<n<100K | |
| # Kimbundu Sentiment Corpus | |
| ## Dataset Description | |
| This dataset contains sentiment-labeled text data in Kimbundu for binary sentiment classification (Positive/Negative). Sentiments are extracted and processed from the English meanings of the sentences using DistilBERT for sentiment classification. The dataset is part of a larger collection of African language sentiment analysis resources. | |
| ## Dataset Statistics | |
| - **Total samples**: 56,896 | |
| - **Positive sentiment**: 31789 (55.9%) | |
| - **Negative sentiment**: 25107 (44.1%) | |
| ## Dataset Structure | |
| ### Data Fields | |
| - **Text Column**: Contains the original text in Kimbundu | |
| - **sentiment**: Sentiment label (Positive or Negative only) | |
| ### Data Splits | |
| This dataset contains a single split with all the processed data. | |
| ## Data Processing | |
| The sentiment labels were generated using: | |
| - Model: `distilbert-base-uncased-finetuned-sst-2-english` | |
| - Processing: Batch processing with optimization for efficiency | |
| - Deduplication: Duplicate entries were removed based on text content | |
| - **Filtering**: Only Positive and Negative sentiments retained for binary classification | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| # Load the dataset | |
| dataset = load_dataset("michsethowusu/kimbundu-sentiments-corpus") | |
| # Access the data | |
| print(dataset['train'][0]) | |
| # Check sentiment distribution | |
| from collections import Counter | |
| sentiments = [item['sentiment'] for item in dataset['train']] | |
| print(Counter(sentiments)) | |
| ``` | |
| ## Use Cases | |
| This dataset is ideal for: | |
| - Binary sentiment classification tasks | |
| - Training sentiment analysis models for Kimbundu | |
| - Cross-lingual sentiment analysis research | |
| - African language NLP model development | |
| ## Citation | |
| If you use this dataset in your research, please cite: | |
| ```bibtex | |
| @dataset{kimbundu_sentiments_corpus, | |
| title={Kimbundu Sentiment Corpus}, | |
| author={Mich-Seth Owusu}, | |
| year={2025}, | |
| url={https://huggingface.co/datasets/michsethowusu/kimbundu-sentiments-corpus} | |
| } | |
| ``` | |
| ## License | |
| This dataset is released under the MIT License. | |
| ## Contact | |
| For questions or issues regarding this dataset, please open an issue on the dataset repository. | |
| ## Dataset Creation | |
| **Date**: 2025-07-02 | |
| **Processing Pipeline**: Automated sentiment analysis using HuggingFace Transformers | |
| **Quality Control**: Deduplication, batch processing optimizations, and binary sentiment filtering applied | |