Eshrag Refaee

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2016

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iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases
Eshrag Refaee | Verena Rieser
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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Benchmarking Machine Translated Sentiment Analysis for Arabic Tweets
Eshrag Refaee | Verena Rieser
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop

2014

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An Arabic Twitter Corpus for Subjectivity and Sentiment Analysis
Eshrag Refaee | Verena Rieser
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present a newly collected data set of 8,868 gold-standard annotated Arabic feeds. The corpus is manually labelled for subjectivity and sentiment analysis (SSA) ( = 0:816). In addition, the corpus is annotated with a variety of motivated feature-sets that have previously shown positive impact on performance. The paper highlights issues posed by twitter as a genre, such as mixture of language varieties and topic-shifts. Our next step is to extend the current corpus, using online semi-supervised learning. A first sub-corpus will be released via the ELRA repository as part of this submission.

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Evaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds
Eshrag Refaee | Verena Rieser
Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP)

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