aclImdb_v1 Large Movie Review Dataset

AclImdb – v1 Dataset is a large-scale movie review dataset for binary sentiment classification. It covers more data than the benchmark dataset, with 25,000 movie reviews for training and 25,000 for testing. Additional unlabeled data is also available. The dataset contains both raw text and processed word bag formats.

The AclImdb-v1 dataset was released by the Stanford AI Lab in 2011 in the Proceedings of the 49th Annual Conference of the Association for Computational Linguistics: Human Language Technologies. The main publishers are Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng and Christopher Potts. The related paper is "Learning Word Vectors for Sentiment Analysis".