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# Dataset Card for Dataset Name |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** https://github.com/americanas-tech/b2w-reviews01 |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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B2W-Reviews01 is an open corpus of product reviews. It contains more than 130k e-commerce customer reviews, collected from the Americanas.com website between January and May, 2018. B2W-Reviews01 offers rich information about the reviewer profile, such as gender, age, and geographical location. The corpus also has two different review rates: |
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* the usual 5-point scale rate, represented by stars in most e-commerce websites, |
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* a "recommend to a friend" label, a "yes or no" question representing the willingness of the customer to recommend the product to someone else. |
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This dataset can be useful for several Natural Language Processing (NLP)/ Computational Linguistics (CL) tasks. The first that comes to mind is probably sentiment analysis. Sentiment analysis is the task of assigning a sentiment (or a position) to the content of a given text. For this task, B2W-Reviews01 offers the two distinct evaluation ratings. |
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### Supported Tasks and Leaderboards |
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* Sentiment Analysis |
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* Topic Modeling |
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### Languages |
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* Portuguese |
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## Dataset Structure |
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### Data Instances |
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``` |
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{'submission_date': '2018-01-02 06:23:22', |
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'reviewer_id': '6adc7901926fc1697d34181fbd88895976b4f3f31f0102d90217d248a1fad156', |
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'product_id': '123911277', |
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'product_name': 'Triciclo Gangorra Belfix Cabeça Cachorro Rosa', |
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'product_brand': 'belfix', |
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'site_category_lv1': 'Brinquedos', |
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'site_category_lv2': 'Mini Veículos', |
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'review_title': 'O produto não foi entregue', |
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'overall_rating': 1, |
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'recommend_to_a_friend': 'Yes', |
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'review_text': 'Incrível o descaso com o consumidor. O produto não chegou, apesar de já ter sido pago. Não recebo qualquer informação sobre onde se encontra o produto, ou qualquer compensação do vendedor. Não recomendo.', |
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'reviewer_birth_year': 1981, |
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'reviewer_gender': 'M', |
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'reviewer_state': 'RJ'} |
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``` |
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### Data Fields |
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* **submission_date**: the date and time when the review was submitted. |
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* **reviewer_id**: a unique identifier for the reviewer. |
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* **product_id**: a unique identifier for the product being reviewed. |
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* **product_name**: the name of the product being reviewed. |
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* **product_brand**: the brand of the product being reviewed. |
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* **site_category_lv1**: the highest level category for the product on the site where the review is being submitted. |
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* **site_category_lv2**: the second level category for the product on the site where the review is being submitted. |
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* **review_title**: the title of the review. |
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* **overall_rating**: the overall star rating given by the reviewer on a scale of 1 to 5. |
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* **recommend_to_a_friend**: whether or not the reviewer would recommend the product to a friend (Yes/No). |
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* **review_text**: the full text of the review. |
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* **reviewer_birth_year**: the birth year of the reviewer. |
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* **reviewer_gender**: the gender of the reviewer (F/M). |
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* **reviewer_state**: the Brazilian state of the reviewer (e.g. RJ). |
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### Data Splits |
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### Citation Information |
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``` |
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@inproceedings{real2019b2w, |
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title={B2W-reviews01: an open product reviews corpus}, |
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author={Real, Livy and Oshiro, Marcio and Mafra, Alexandre}, |
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booktitle={STIL-Symposium in Information and Human Language Technology}, |
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year={2019} |
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} |
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``` |
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### Contributions |
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Thanks to [@ruanchaves](https://github.com/ruanchaves) for adding this dataset. |
