| --- |
| license: mit |
| task_categories: |
| - text-classification |
| language: |
| - tso |
| tags: |
| - sentiment |
| - african-languages |
| - nlp |
| - text-classification |
| - binary-classification |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # Tsonga Sentiment Corpus |
|
|
| ## Dataset Description |
|
|
| This dataset contains sentiment-labeled text data in Tsonga 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**: 255,067 |
| - **Positive sentiment**: 151905 (59.6%) |
| - **Negative sentiment**: 103162 (40.4%) |
|
|
| ## Dataset Structure |
|
|
| ### Data Fields |
|
|
| - **Text Column**: Contains the original text in Tsonga |
| - **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/tsonga-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 Tsonga |
| - Cross-lingual sentiment analysis research |
| - African language NLP model development |
|
|
| ## Citation |
|
|
| If you use this dataset in your research, please cite: |
|
|
| ```bibtex |
| @dataset{tsonga_sentiments_corpus, |
| title={Tsonga Sentiment Corpus}, |
| author={Mich-Seth Owusu}, |
| year={2025}, |
| url={https://huggingface.co/datasets/michsethowusu/tsonga-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 |
|
|
