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