Multi-domain data set of reviews for sentiment classification

This is a data set of reviews from multiple sources used for text sentiment classification. The text samples have been preprocessed, tokenized (such that tokens can be obtained by splitting the text on whitespaces), and split into sentences, and then also labeled as either negative (Class 0) or positive (Class 1). The sets are organized into two categories: Primary and Additional sets. The data sets in the Primary category can be used standalone with the standard training, validation, and test set splits. The data sets in the Additional category are inteded for classifier training, in order to provide additional features for sentiment classification to improve classification performance of the Primary sets. These sets contain a training set and a validation set only. The Primary category includes airline reviews, airport reviews, hotel reviews, and restaurant reviews. The Additional category includes movie reviews (from Rotten Tomatoes) and product reviews (from Amazon). The raw data sets were obtained from the following sources: https://www.kaggle.com/datasets/andrezaza/clapper-massive-rotten-tomatoes-movies-and-reviews/ https://www.kaggle.com/datasets/bwandowando/rotten-tomatoes-9800-movie-critic-and-user-reviews/ https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023 https://github.com/quankiquanki/skytrax-reviews-dataset/tree/master https://www.cs.cmu.edu/~jiweil/html/hotel-review.html https://www.kaggle.com/datasets/farukalam/yelp-restaurant-reviews?select=Yelp+Restaurant+Reviews.csv