118 datasets found

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

The dataset on which this article is based are offered by [3]. The sources of information are: The financial time series of the SPDR S&P 500 ETF (SPY), a fund replicating...

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

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

EmoLex

Global Sentiment Analysis Of COVID-19 Tweets Over Time

Semeval-2016 Task 6: Detecting stance in tweets.

The MemoSEN dataset is a multimodal dataset for sentiment analysis of Bengali memes.

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...

Multi-ZOL is a Chinese dataset for Target-oriented Multimodal Sentiment Classification (TMSC). The dataset contains text and image data, where the text data is used to determine...

Twitter15 and Twitter17 are two English datasets for Target-oriented Multimodal Sentiment Classification (TMSC). The datasets contain text and image data, where the text data is...

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

The Memotion Dataset 7K is a collection of 7000 memes with associated metadata.

The dataset used in the paper is a collection of unstructured text data from social networks, news sites, and forums.

The Polarity dataset contains text documents with sentiment labels.

The dataset used in the paper for instruction tuning of Large Language Models (LLMs) during instruction tuning.

The IMDb review dataset is used for positive generation task.

Annotating expressions of opinions and emotions in language