@inproceedings{c0604246726f4991a6d69cf32244d185,
title = "Annotating targets of opinions in arabic using crowdsourcing",
abstract = "We present a method for annotating targets of opinions in Arabic in a two-stage process using the crowdsourcing tool Amazon Mechanical Turk. The first stage consists of identifying candidate targets {"}entities{"} in a given text. The second stage consists of identifying the opinion polarity (positive, negative, or neutral) expressed about a specific entity. We annotate a corpus of Arabic text using this method, selecting our data from online commentaries in different domains. Despite the complexity of the task, we find high agreement. We present detailed analysis.",
author = "Noura Farra and Kathleen McKeown and Nizar Habash",
note = "Funding Information: This work was made possible by grant NPRP 6-716-1-138 from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made are solely the responsibility of the authors. We thank anonymous reviewers for their helpful comments. We would also like to thank Debanjan Ghosh, Owen Rambow, and Ramy Es-kander for helpful discussions and feedback. We thank the AMT annotators for all their hard work, insightful questions, and for continuing to participate in multiple rounds of our annotation tasks. Publisher Copyright: {\textcopyright} ACL 2015. All rights reserved.; 2nd Workshop on Arabic Natural Language Processing, ANLP 2015 ; Conference date: 30-07-2015",
year = "2015",
language = "English (US)",
series = "2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "89--98",
editor = "Nizar Habash and Stephan Vogel and Kareem Darwish",
booktitle = "2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings",
}