21 datasets found

The dataset used in this paper is SST-2, Irony, IronyB, TREC6, and SNIPS.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a variety of datasets for semi-supervised learning tasks.

The dataset used in the paper is a large-scale corpus of movie reviews from the Socher et al. (2013) dataset.

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

The Amazon dataset is used to evaluate the performance of the proposed approach. It consists of 2000 users, 1500 items, 86690 reviews, 7219 number ratings, 3.6113 average number...

Text classification dataset

Text, tabular and image classification datasets

The Tweet Sentiment Extraction dataset contains positive, negative, and neutral tweets with human-annotated rationales.

The Movie Reviews dataset contains positive and negative movie reviews with rationales annotated by humans to support classification.

The dataset consists of 25000 reviews from IMDb.

The Yelp review dataset contains hotel and restaurant reviews filtered (spam) and recommended (legitimate) by Yelp.

The TEL-NLP dataset is a collection of Telugu text data for four NLP tasks: sentiment analysis, emotion identification, hate speech detection, and sarcasm detection.

The Yelp Dataset contains 1.6M reviews and 500K tips by 366K users for 61K businesses; 481K business attributes, such as hours, parking availability, ambience; and check-ins for...

The IMDB sentiment classification dataset is used for text classification tasks.

The dataset used for sentiment analysis and topic classification tasks.

The Yelp dataset challenge contains reviews and images of restaurants, with the goal of recommending images for each review.

The dataset used for the experiments across ten models– ranging from bag-of-words models to pre-trained transformers– and find that a model having higher AUC does not necessarily...

The dataset used in the paper is a language domain dataset, specifically for sentiment classification, named AG News. The dataset is used to evaluate the performance of...

The Penn Treebank dataset contains one million words of 1989 Wall Street Journal material annotated in Treebank II style, with 42k sentences of varying lengths.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors tested the proposed method on three real data sets for the most relevant security...