118 datasets found

The WASSA 2017 Emotion Intensity Shared task dataset is a collection of 7097 annotated tweets, classified into 4 categories: joy, anger, fear, and sadness.

The dataset is created from raw financial datasets, including price data, financials, and sentiment data.

The dataset used in the paper is the Stanford Sentiment Treebank (SST) dataset, which contains standard train/dev/test sets and two subtasks: binary sentence classification or...

The Jester dataset contains joke ratings in a continuous scale from 1 to 10 for 100 jokes from a total of 73421 users.

The SemEval-2017 Task 4 dataset consists of tweets with sentiment labels.

Sentiment analysis dataset for Twitter

Opinion mining and sentiment analysis dataset

Twitter sentiment analysis dataset for SemEval-2016 Task 4

The Ciao product review dataset contains product reviews labeled as positive, negative, or neutral.

The SemEval Twitter sentiment datasets contain tweets labeled as positive, negative, or neutral.

The paper proposes a novel approach to the sequential example selection paradigm for in-context learning.

Chinese sentiment classification and entailment models

The Tweet Emotion Intensity Dataset was created using best–worst scaling and crowdsourcing.

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...

The GoEmotions dataset, a collection of 58k Reddit comments labeled according to the publisher affect from a taxonomy of 28 emotions.

The dataset used in the paper is a real-world dataset for sentiment analysis.

The dataset used in this paper for sentiment analysis.

Sentiment in Twitter events.

The Twitter Dataset is a collection of tweets annotated with Plutchik's emotions, consisting of tweets in three different languages: English, Dutch, and German.

A newly created corpus of discussions from Wikipedia Talk pages for dispute detection