Annotating targets of opinions in arabic using crowdsourcing

Noura Farra, Kathleen McKeown, Nizar Habash

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

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.

Original languageEnglish (US)
Title of host publication2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings
EditorsNizar Habash, Stephan Vogel, Kareem Darwish
PublisherAssociation for Computational Linguistics (ACL)
Pages89-98
Number of pages10
ISBN (Electronic)9781941643587
StatePublished - 2015
Event2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - Beijing, China
Duration: Jul 30 2015 → …

Publication series

Name2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings

Conference

Conference2nd Workshop on Arabic Natural Language Processing, ANLP 2015
Country/TerritoryChina
CityBeijing
Period7/30/15 → …

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Software

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