Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
100K - 1M
ArXiv:
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| language: | |
| - en | |
| license: | |
| - other | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 100K<n<1M | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - sentiment-classification | |
| pretty_name: YelpReviewFull | |
| license_details: yelp-licence | |
| dataset_info: | |
| config_name: yelp_review_full | |
| features: | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 1 star | |
| '1': 2 star | |
| '2': 3 stars | |
| '3': 4 stars | |
| '4': 5 stars | |
| - name: text | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 483811554 | |
| num_examples: 650000 | |
| - name: test | |
| num_bytes: 37271188 | |
| num_examples: 50000 | |
| download_size: 322952369 | |
| dataset_size: 521082742 | |
| configs: | |
| - config_name: yelp_review_full | |
| data_files: | |
| - split: train | |
| path: yelp_review_full/train-* | |
| - split: test | |
| path: yelp_review_full/test-* | |
| default: true | |
| train-eval-index: | |
| - config: yelp_review_full | |
| task: text-classification | |
| task_id: multi_class_classification | |
| splits: | |
| train_split: train | |
| eval_split: test | |
| col_mapping: | |
| text: text | |
| label: target | |
| metrics: | |
| - type: accuracy | |
| name: Accuracy | |
| - type: f1 | |
| name: F1 macro | |
| args: | |
| average: macro | |
| - type: f1 | |
| name: F1 micro | |
| args: | |
| average: micro | |
| - type: f1 | |
| name: F1 weighted | |
| args: | |
| average: weighted | |
| - type: precision | |
| name: Precision macro | |
| args: | |
| average: macro | |
| - type: precision | |
| name: Precision micro | |
| args: | |
| average: micro | |
| - type: precision | |
| name: Precision weighted | |
| args: | |
| average: weighted | |
| - type: recall | |
| name: Recall macro | |
| args: | |
| average: macro | |
| - type: recall | |
| name: Recall micro | |
| args: | |
| average: micro | |
| - type: recall | |
| name: Recall weighted | |
| args: | |
| average: weighted | |
| --- | |
| # Dataset Card for YelpReviewFull | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [Yelp](https://www.yelp.com/dataset) | |
| - **Repository:** [Crepe](https://github.com/zhangxiangxiao/Crepe) | |
| - **Paper:** [Character-level Convolutional Networks for Text Classification](https://arxiv.org/abs/1509.01626) | |
| - **Point of Contact:** [Xiang Zhang](mailto:[email protected]) | |
| ### Dataset Summary | |
| The Yelp reviews dataset consists of reviews from Yelp. | |
| It is extracted from the Yelp Dataset Challenge 2015 data. | |
| ### Supported Tasks and Leaderboards | |
| - `text-classification`, `sentiment-classification`: The dataset is mainly used for text classification: given the text, predict the sentiment. | |
| ### Languages | |
| The reviews were mainly written in english. | |
| ## Dataset Structure | |
| ### Data Instances | |
| A typical data point, comprises of a text and the corresponding label. | |
| An example from the YelpReviewFull test set looks as follows: | |
| ``` | |
| { | |
| 'label': 0, | |
| 'text': 'I got \'new\' tires from them and within two weeks got a flat. I took my car to a local mechanic to see if i could get the hole patched, but they said the reason I had a flat was because the previous patch had blown - WAIT, WHAT? I just got the tire and never needed to have it patched? This was supposed to be a new tire. \\nI took the tire over to Flynn\'s and they told me that someone punctured my tire, then tried to patch it. So there are resentful tire slashers? I find that very unlikely. After arguing with the guy and telling him that his logic was far fetched he said he\'d give me a new tire \\"this time\\". \\nI will never go back to Flynn\'s b/c of the way this guy treated me and the simple fact that they gave me a used tire!' | |
| } | |
| ``` | |
| ### Data Fields | |
| - 'text': The review texts are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n". | |
| - 'label': Corresponds to the score associated with the review (between 1 and 5). | |
| ### Data Splits | |
| The Yelp reviews full star dataset is constructed by randomly taking 130,000 training samples and 10,000 testing samples for each review star from 1 to 5. | |
| In total there are 650,000 trainig samples and 50,000 testing samples. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| The Yelp reviews full star dataset is constructed by Xiang Zhang ([email protected]) from the Yelp Dataset Challenge 2015. It is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| You can check the official [yelp-dataset-agreement](https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf). | |
| ### Citation Information | |
| Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). | |
| ### Contributions | |
| Thanks to [@hfawaz](https://github.com/hfawaz) for adding this dataset. |