Rotten Tomatoes Reviews Dataset

Content This rating inference dataset is a sentiment classification dataset, containing 5,331 positive and 5,331 negative processed sentences from Rotten Tomatoes movie reviews. On average, these reviews consist of 21 words.

Acknowledgements This dataset is converted to a csv file by using the data descriped in the paper of Pang and Lee (2005) which is frequently used as a benchmark for text classification tasks. Also, special thanks to Product School for enabling the photo used in the banner for public use.

References Bo Pang and Lillian Lee. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05), pages 115–124, Ann Arbor, Michigan, June 2005. Association for Computational Linguistics

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Original Data Source: Rotten Tomatoes Reviews Dataset