25 datasets found

The dataset used for user-level stance detection, comprising over 100 million tweets.

The Online Media Monitor (OMM) from the University of Hamburg contributed with a dataset of 5,236,660 unlabeled tweets gathered from June 21, 2022, to December 8, 2022.

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.

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

A dataset of geolocated tweets in 2022, filtered to keep only tweets in the UK.

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

The dataset consists of tweets posted by 212 Twitter users during and after their pregnancy.

The dataset consists of tweets posted by 212 Twitter users during and after their pregnancy.

The dataset consists of tweets posted by 212 Twitter users during and after their pregnancy.

The dataset consists of tweets posted by 212 Twitter users during and after their pregnancy.

The dataset consists of tweets posted by 212 Twitter users during and after their pregnancy.

The dataset consists of all tweets posted by 212 Twitter users during and after their pregnancy.

The Dynamic dataset, a collection of tweets generated using a human-and-model-in-the-loop process, containing challenging perturbations.

The Waseem dataset, a collection of tweets containing hate speech, with a focus on sexist and racist language.

The 2018 dataset used in the BioCreative VII Track 3 - automatic extraction of medication names in tweets.

The dataset used in the BioCreative VII Track 3 - automatic extraction of medication names in tweets.

The dataset used in the paper for stock movement and volatility prediction from tweets, macroeconomic factors and historical prices.

The dataset used in this paper is a collection of Twitter data, including tweets, retweets, and replies.

The dataset used in this paper is a collection of social media data from Twitter, including user profiles, follow links, and tweets.

Stream TwitterSentiment is a dataset of tweets, focusing on sentiment analysis, and is used to test the performance of active stream learning algorithms for polarity learning.