ASTD: Arabic sentiment tweets dataset

Mahmoud Nabil; Mohamed Aly; Amir F. Atiya

doi:10.18653/v1/d15-1299

ASTD: Arabic sentiment tweets dataset

Mahmoud Nabil, Mohamed Aly, Amir F. Atiya

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

317 Scopus citations

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.

Original language	English (US)
Title of host publication	Conference Proceedings - EMNLP 2015
Subtitle of host publication	Conference on Empirical Methods in Natural Language Processing
Publisher	Association for Computational Linguistics (ACL)
Pages	2515-2519
Number of pages	5
ISBN (Electronic)	9781941643327
DOIs	https://doi.org/10.18653/v1/d15-1299
State	Published - 2015
Event	Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal Duration: Sep 17 2015 → Sep 21 2015

Publication series

Name	Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Other

Other	Conference on Empirical Methods in Natural Language Processing, EMNLP 2015
Country/Territory	Portugal
City	Lisbon
Period	09/17/15 → 09/21/15

Bibliographical note

Publisher Copyright:
© 2015 Association for Computational Linguistics.

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Information Systems

Access to Document

10.18653/v1/d15-1299

Cite this

Nabil, M., Aly, M., & Atiya, A. F. (2015). ASTD: Arabic sentiment tweets dataset. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 2515-2519). (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1299

@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)",

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booktitle = "Conference Proceedings - EMNLP 2015",

address = "United States",

}

Nabil, M, Aly, M & Atiya, AF 2015, ASTD: Arabic sentiment tweets dataset. in Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing. Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics (ACL), pp. 2515-2519, Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, 09/17/15. https://doi.org/10.18653/v1/d15-1299

ASTD: Arabic sentiment tweets dataset. / Nabil, Mahmoud; Aly, Mohamed; Atiya, Amir F.
Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), 2015. p. 2515-2519 (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2015

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AB - 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.

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ASTD: Arabic sentiment tweets dataset

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