96 datasets found

NLI and review classification datasets used for character-level translation experiments

The Twitter Climate Change Sentiment Dataset contains labelled tweets pertaining to climate change, covering the time period from April 27, 2015, to February 21, 2018.

Movie Review (MR) dataset is a binary sentiment classification dataset with movie reviews from IMDB, consisting of 1000 positive and 1000 negative movie reviews. Product Review...

A dataset for sentiment analysis of Yoruba movie reviews.

A dataset of 16,000 tweets, of which 3,383 tweets were sexist.

Stanford Sentiment Treebank Binary (SST-2) and Internet Movie Database (IMDb) datasets for sentiment classification.

The dataset used in the paper for sentiment analysis in cross-language and cross-domain settings.

A dialogue dataset annotated with fact-check-needed label (DDFC) for detecting sentences that do not require factual correctness judgment

The BBC News dataset was used for sentiment analysis of news articles.

A manually labelled dataset of 124,360 weather tweets collected by Asiaee T. et al. (2012) as part of the "Dialogue Earth" project.

A new approach to sentiment analysis that takes context into account by combining the dictionaries generated by SocialSent with the scoring rules and base sentiment dictionary...

Twitter Airline Data dataset contains sentiment values on a scale of 0-2.

Internal feedback data (IFD) gathered by the company on healthcare applications. IFD contains complaints and feedback collected from customers along with sentiment score...

The dataset is a corpus of movie reviews and anonymous imageboard messages annotated with consideration of containing or not state of aggression.

The Yelp Reviews Polarity dataset contains 560k and 38k (in training and dev portion respectively) customer reviews in English from Yelp.

Semeval-2016 Task 6: Detecting stance in tweets.

The dataset used for sentiment analysis of climate change-related tweets.

The Rotten Tomatoes dataset has 5331 positive and 5331 negative review sentences.

The SST2 dataset has 6920/872/1821 example sentences in the train/dev/test sets. The task is binary classification into positive/negative sentiment. The IMDB dataset has...

The dataset used for training a text classifier to learn the polarity of hotel reviews.