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An analytical study of Arabic sentiments: Maktoob case study

  • Zarqa University
  • Jordan University of Science and Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

46 Scopus citations

Abstract

The problem of automatically extracting opinions and emotions from textual data have gained a lot of interest recently. Unfortunately, most studies on Sentiment Analysis (SA) focus mainly on the English language, whereas studies considering other important and wide-spread languages such as Arabic are few. Moreover, publicly-available Arabic datasets are seldom found on the Web. In this work, a labeled dataset of Arabic reviews/comments is collected from a social networking website (Yahoo!-Maktoob). A detailed analysis of different aspects of the collected dataset such as the reviews' length, the numbers of likes/dislikes, the polarity distribution and the languages used is presented. Finally, the dataset is used to test popular classifiers commonly used for SA.

Original languageEnglish
Title of host publication2013 8th International Conference for Internet Technology and Secured Transactions, ICITST 2013
PublisherIEEE Computer Society
Pages89-94
Number of pages6
ISBN (Print)9781908320209
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 8th International Conference for Internet Technology and Secured Transactions, ICITST 2013 - Yangzhou, Jiangsu, China
Duration: 23 Mar 201325 Mar 2013

Publication series

Name2013 8th International Conference for Internet Technology and Secured Transactions, ICITST 2013

Conference

Conference2013 8th International Conference for Internet Technology and Secured Transactions, ICITST 2013
Country/TerritoryChina
CityYangzhou, Jiangsu
Period23/03/1325/03/13

Keywords

  • Arabic text analysis
  • document-level sentiment analysis
  • social network

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