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  license: cc-by-sa-4.0
 
 
 
 
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  license: cc-by-sa-4.0
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+ task_categories:
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+ - text-classification
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+ task_ids:
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+ - sentiment-classification
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  ---
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+
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+ # Dataset Card for "rotten_tomatoes_reviews"
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Additional Information](#additional-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [http://www.cs.cornell.edu/people/pabo/movie-review-data/](http://www.cs.cornell.edu/people/pabo/movie-review-data/)
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+ - **Paper:** [https://arxiv.org/abs/cs/0506075](https://arxiv.org/abs/cs/0506075)
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+
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+ ### Dataset Summary
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+
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+ Movie Review Dataset.
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+
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+ This is a dataset containing 4,265 positive and 4,265 negative processed
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+ sentences from Rotten Tomatoes movie reviews.
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+
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+ The data fields are the same among all splits.
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+
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+ #### default
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+ - `text`: a `string` feature.
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+ - `label`: a classification label, with possible values including `neg` (0), `pos` (1).
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+
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+ ### Data Splits
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+
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+ | name |train|validation|test|
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+ |-------|----:|---------:|---:|
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+ |default| 8530| 1066|1066|
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+
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+ ## Additional Information
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+
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+ ### Citation Information
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+
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+ ```
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+ @InProceedings{Pang+Lee:05a,
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+ author = {Bo Pang and Lillian Lee},
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+ title = {Seeing stars: Exploiting class relationships for sentiment
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+ categorization with respect to rating scales},
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+ booktitle = {Proceedings of the ACL},
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+ year = 2005
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+ }
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+
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+ ```