Dataset Card for YelpReviewFull

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 ( xiang.zhang@nyu.edu ) 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 .

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 for adding this dataset.