• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations | Disambiguate

DMCA

Subjectivity and Sentiment Annotation of Modern Standard Arabic

Cached

  • Download as a PDF

Download Links

  • [aclweb.org]
  • [www.aclweb.org]
  • [aclweb.org]
  • [www.aclweb.org]
  • [aclweb.org]
  • [wing.comp.nus.edu.sg]
  • [www.aclweb.org]
  • [www.seas.gwu.edu]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Muhammad Abdul-mageed , Mona T. Diab
Citations:12 - 1 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Abdul-mageed_subjectivityand,
    author = {Muhammad Abdul-mageed and Mona T. Diab},
    title = {Subjectivity and Sentiment Annotation of Modern Standard Arabic},
    year = {}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Subjectivity and sentiment analysis (SSA) is an area that has been witnessing a flurry of novel research. However, only few attempts have been made to build SSA systems for morphologically-rich languages (MRL). In the current study, we report efforts to partially bridge this gap. We present a newly labeled corpus of Modern Standard Arabic (MSA) from the news domain manually annotated for subjectivity and domain at the sentence level. We summarize our linguisticallymotivated annotation guidelines and provide examples from our corpus exemplifying the different phenomena. Throughout the paper, we discuss expression of subjectivity in natural language, combining various previously scattered insights belonging to many branches of linguistics. 1

Keyphrases

modern standard arabic    sentiment annotation    morphologically-rich language    sentence level    current study    many branch    different phenomenon    news domain    sentiment analysis    linguisticallymotivated annotation guideline    ssa system    novel research    natural language   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University