The corpus Twitter for Sentiment Analysis is a collection of tweets containing text and images collected from July to December 2016. During this time span, Twitter’s Sample API were exploited to access a random 1% sample of the stream of all globally produced tweets. At the end of the data collection process, the total number of tweets in the dataset is ~3.4M, corresponding to ~4M images. Each tweet (text and associated images) has been labeled according to the sentiment polarity of the text, obtaining a labeled set of tweets and images divided in 3 categories. The tweets having the most confident textual sentiment predictions have been selected to build a Twitter for Sentiment Analysis (T4SA) dataset.
