Evaluating social context in Arabic opinion mining
Joint Authors
Wahshih, Haydar
Khasawinah, Rawan
al-Smadi, Izzat
al-Kabi, Muhammad
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 6 (30 Nov. 2018)9 p.
Publisher
Publication Date
2018-11-30
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
This study is based on a benchmark corpora consisting of 3,015 textual Arabic opinions collected from Facebook.
These collected Arabic opinions are distributed equally among three domains (Food, Sport, and Weather), to create a balanced benchmark corpus.
To accomplish this study ten Arabic lexicons were constructed manually, and a new tool called Arabic Opinions Polarity Identification (AOPI) is designed and implemented to identify the polarity of the collected Arabic opinions using the constructed lexicons.
Furthermore, this study includes a comparison between the constructed tool and two free online sentiment analysis tools (SocialMention and SentiStrength) that support the Arabic language.
The effect of stemming on the accuracy of these tools is tested in this study.
The evaluation results using machine learning classifiers show that AOPI is more effective than the other two free online sentiment analysis tools using a stemmed dataset
American Psychological Association (APA)
al-Kabi, Muhammad& al-Smadi, Izzat& Khasawinah, Rawan& Wahshih, Haydar. 2018. Evaluating social context in Arabic opinion mining. The International Arab Journal of Information Technology،Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874036
Modern Language Association (MLA)
al-Kabi, Muhammad…[et al.]. Evaluating social context in Arabic opinion mining. The International Arab Journal of Information Technology Vol. 15, no. 6 (Nov. 2018).
https://search.emarefa.net/detail/BIM-874036
American Medical Association (AMA)
al-Kabi, Muhammad& al-Smadi, Izzat& Khasawinah, Rawan& Wahshih, Haydar. Evaluating social context in Arabic opinion mining. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874036
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-874036