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Add dataset README for sentiment corpus

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  ---
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- dataset_info:
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- features:
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- - name: Afrikaans
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- dtype: string
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- - name: sentiment
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 152245554
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- num_examples: 1500000
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- download_size: 0
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- dataset_size: 152245554
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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  ---
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- # Dataset Card for "afrikaans-sentiments-corpus"
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- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: mit
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+ task_categories:
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+ - text-classification
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+ language:
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+ - afr
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+ tags:
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+ - sentiment
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+ - african-languages
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+ - nlp
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+ - text-classification
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+ - binary-classification
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+ size_categories:
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+ - 1M<n<10M
 
 
 
 
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  ---
 
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+ # Afrikaans Sentiment Corpus
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+
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+ ## Dataset Description
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+
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+ This dataset contains sentiment-labeled text data in Afrikaans 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.
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+
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+ ## Dataset Statistics
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+
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+ - **Total samples**: 1,500,000
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+ - **Positive sentiment**: 803944 (53.6%)
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+ - **Negative sentiment**: 696056 (46.4%)
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+
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+ - **Text Column**: Contains the original text in Afrikaans
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+ - **sentiment**: Sentiment label (Positive or Negative only)
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+
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+ ### Data Splits
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+
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+ This dataset contains a single split with all the processed data.
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+
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+ ## Data Processing
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+
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+ The sentiment labels were generated using:
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+ - Model: `distilbert-base-uncased-finetuned-sst-2-english`
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+ - Processing: Batch processing with optimization for efficiency
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+ - Deduplication: Duplicate entries were removed based on text content
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+ - **Filtering**: Only Positive and Negative sentiments retained for binary classification
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the dataset
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+ dataset = load_dataset("michsethowusu/afrikaans-sentiments-corpus")
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+
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+ # Access the data
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+ print(dataset['train'][0])
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+
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+ # Check sentiment distribution
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+ from collections import Counter
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+ sentiments = [item['sentiment'] for item in dataset['train']]
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+ print(Counter(sentiments))
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+ ```
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+
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+ ## Use Cases
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+
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+ This dataset is ideal for:
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+ - Binary sentiment classification tasks
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+ - Training sentiment analysis models for Afrikaans
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+ - Cross-lingual sentiment analysis research
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+ - African language NLP model development
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+
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+ ## Citation
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+
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+ If you use this dataset in your research, please cite:
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+
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+ ```bibtex
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+ @dataset{afrikaans_sentiments_corpus,
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+ title={Afrikaans Sentiment Corpus},
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+ author={Mich-Seth Owusu},
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+ year={2025},
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+ url={https://huggingface.co/datasets/michsethowusu/afrikaans-sentiments-corpus}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This dataset is released under the MIT License.
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+
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+ ## Contact
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+
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+ For questions or issues regarding this dataset, please open an issue on the dataset repository.
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+
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+ ## Dataset Creation
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+
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+ **Date**: 2025-07-02
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+ **Processing Pipeline**: Automated sentiment analysis using HuggingFace Transformers
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+ **Quality Control**: Deduplication, batch processing optimizations, and binary sentiment filtering applied