@inproceedings{43d2a7e9f067430b9965f85770336ffa,
title = "ASTD: Arabic sentiment tweets dataset",
abstract = "This paper introduces ASTD, an Arabic social sentiment analysis dataset gathered from Twitter. It consists of about 10,000 tweets which are classified as objective, subjective positive, subjective negative, and subjective mixed. We present the properties and the statistics of the dataset, and run experiments using standard partitioning of the dataset. Our experiments provide benchmark results for 4 way sentiment classification on the dataset.",
author = "Mahmoud Nabil and Mohamed Aly and Atiya, {Amir F.}",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics.; Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 ; Conference date: 17-09-2015 Through 21-09-2015",
year = "2015",
doi = "10.18653/v1/d15-1299",
language = "English (US)",
series = "Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing",
publisher = "Association for Computational Linguistics (ACL)",
pages = "2515--2519",
booktitle = "Conference Proceedings - EMNLP 2015",
address = "United States",
}