1. Multimodal Damage Identification for Humanitarian Computing: 5879 captioned images (image and text) from social media related to damage during natural disasters/wars, and belong to 6 classes: Fires, Floods, Natural landscape, Infrastructural, Human, Non-damage.
2. Sports articles for objectivity analysis: 1000 sports articles were labeled using Amazon Mechanical Turk as objective or subjective. The raw texts, extracted features, and the URLs from which the articles were retrieved are provided.
3. Twitter Data set for Arabic Sentiment Analysis: This problem of Sentiment Analysis (SA) has been studied well on the English language but not Arabic one. Two main approaches have been devised: corpus-based and lexicon-based.