| --- |
| dataset_info: |
| features: |
| - name: text |
| dtype: string |
| - name: label |
| dtype: string |
| - name: source |
| dtype: string |
| - name: domain |
| dtype: string |
| - name: language |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1364685913 |
| num_examples: 3147478 |
| - name: validation |
| num_bytes: 170841288 |
| num_examples: 393435 |
| - name: test |
| num_bytes: 170338153 |
| num_examples: 393436 |
| download_size: 988308759 |
| dataset_size: 1705865354 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| language: |
| - ar |
| - de |
| - en |
| - es |
| - fr |
| - hi |
| - id |
| - it |
| - ko |
| - ms |
| - pt |
| - ru |
| - tr |
| - vi |
| - zh |
| - ja |
| tags: |
| - sentiment |
| - multilingual |
| - emotion |
| - review |
| - classification |
| pretty_name: text |
| size_categories: |
| - 1M<n<10M |
| --- |
| ## Overview |
| **MultilingualSentiment** is a sentiment classification dataset that encompasses three sentiment labels: **Positive**, **Neutral**, **Negative** |
|
|
| The dataset spans multiple languages and covers a wide range of domains, making it ideal for multilingual sentiment analysis tasks. |
|
|
|
|
| ## Dataset Information |
| The dataset was meticulously collected and aggregated from various sources, including Hugging Face and Kaggle. These sources provide diverse languages and domains to ensure a comprehensive and balanced dataset. |
|
|
| - **Total records**: 3,934,349 |
| - The dataset is divided into three subsets: train, validation, and test, with a ratio of 8:1:1: |
| + Train: 3,147,478 |
| + Validation: 393,435 |
| + Test: 393,436 |
|
|
| ### Number of Records per Language |
| | Language | Count | |
| |---------------|---------| |
| | Arabic (ar) | 208,375 | |
| | German (de) | 212,853 | |
| | English (en) | 1,519,860 | |
| | Spanish (es) | 222,911 | |
| | French (fr) | 262,645 | |
| | Hindi (hi) | 9,423 | |
| | Indonesian (id) | 12,536 | |
| | Italian (it) | 3,020 | |
| | Japanese (ja) | 335,656 | |
| | Korean (ko) | 259,998 | |
| | Malay (ms) | 6,661 | |
| | Multilingual | 9,391 | |
| | Portuguese (pt) | 49,188 | |
| | Russian (ru) | 205,186 | |
| | Turkish (tr) | 44,743 | |
| | Vietnamese (vi) | 127,068 | |
| | Chinese (zh) | 444,835 | |
|
|
| ### Number of Records per Label |
| | Label | Count | |
| |-----------|----------| |
| | Negative | 1,436,539 | |
| | Neutral | 1,041,512 | |
| | Positive | 1,456,298 | |
|
|
| ## Applications |
| This dataset is well-suited for training and evaluating models in multilingual sentiment analysis, natural language processing (NLP), and domain-specific sentiment classification tasks. |
|
|
| ## Loading dataset |
| ```python |
| from datasets import load_dataset |
| |
| # Load the MultilingualSentiment dataset |
| dataset = load_dataset("clapAI/MultiLingualSentiment") |
| |
| print(dataset) |
| |
| ``` |
|
|
| ``` |
| DatasetDict({ |
| train: Dataset({ |
| features: ['text', 'label', 'source', 'domain', 'language'], |
| num_rows: 3147478 |
| }) |
| validation: Dataset({ |
| features: ['text', 'label', 'source', 'domain', 'language'], |
| num_rows: 393435 |
| }) |
| test: Dataset({ |
| features: ['text', 'label', 'source', 'domain', 'language'], |
| num_rows: 393436 |
| }) |
| }) |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{clapAI2024multilingualsentiment, |
| title = {MultilingualSentiment: A Multilingual Sentiment Classification Dataset}, |
| author = {clapAI}, |
| year = {2024}, |
| url = {https://huggingface.co/datasets/clapAI/MultiLingualSentiment}, |
| description = {A multilingual dataset for sentiment analysis with labels: positive, neutral, negative, covering diverse languages and domains.}, |
| } |
| ``` |
