83 datasets found

The DiscoEval dataset used for evaluating the performance of the DEPTH model on discourse-related tasks.

The dataset used in the paper is Twitter data, which is used for sentiment analysis. The dataset contains user-level sentiments on specific topics.

The pushshift reddit dataset

The IMDB dataset is a polarity dataset for sentiment analysis or text classification, it contains 50000 sentences and their binary class labels, being either "Positive" or...

The dataset used for sentiment analysis, question type classification, and subjectivity classification tasks.

The dataset used for sentiment analysis, question type classification, and subjectivity classification tasks.

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 for sentiment analysis, question type classification, and subjectivity classification tasks.

The Memotion Dataset is an open-sourced dataset containing 14K annotated memes with human-annotated labels.

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 dataset used in the paper is a multilingual dataset for sentiment analysis, specifically the XED dataset.

The dataset used in the paper is a series of datasets introduced in [46], comprising large corpora of product reviews crawled from Amazon.com. Top-level product categories on...

Yelp Reviews is a large dataset of customer reviews.

The Amazon review dataset is used for multi-source domain adaptation. It contains review texts and ratings of bought products. Products are grouped into categories. Following...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a sentiment analysis task on two public benchmark datasets: Rotten Tomatoes...

The dataset used in the paper is the Stanford Natural Language Inference (SNLI) dataset, which consists of 549,367 premise-hypothesis pairs for train/dev/test sets and target...

The dataset used for sentiment analysis, question type classification, and subjectivity classification tasks.

SICK is a dataset for recognizing textual entailment (RTE), containing 4.5K/0.5K/5.0K train/dev/test examples. Each example consists of a hypothesis and a premise, and the goal...

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...

The dataset for structured sentiment analysis, which aims to predict a structured sentiment graph as shown in Figure 1(a), can be formulated into the problem of tuple...