Arabic Gold Standard Twitter Data for Sentiment Analysis

Dataset

Description

6514 Arabic Tweets manually annotated for sentiment (positive, negative, neutral) and features used for classification.
Date made available2014
PublisherEuropean Language Resources Association
Date of data production2014 -

Research Output

  • 3 Conference contribution

A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases

Refaee, E. & Rieser, V., 31 Mar 2016, (Accepted/In press) Proceedings of the 10th International Workshop on Semantic Evaluation. Association for Computational Linguistics

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Benchmarking Machine Translated Sentiment Analysis for Arabic Tweets

Refaee, E. & Rieser, V., 2015, 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, p. 71-78

Research output: Chapter in Book/Report/Conference proceedingConference contribution

An Arabic Twitter Corpus for Subjectivity and Sentiment Analysis

Refaee, E. & Rieser, V., 2014, Proceedings of the 9th International Conference on Language Resources and Evaluation. Calzolari, N. (ed.). European Language Resources Association, p. 2268-2273 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
File

Cite this

Refaee, E. (Creator), Rieser, V. (Creator) (2014). Arabic Gold Standard Twitter Data for Sentiment Analysis. European Language Resources Association. GS2_DataSet_to_HWU(.zip). 10.17861/0e0a6b6b-4892-4c6e-b640-b204e1190cea