Sentiment analysis system for Arabic articles news (SASAAN)
Other Title(s)
نظام لتحليل المقالات العربية الإخبارية
Joint Authors
Farahat, Fawzia Zaki
Hamudah, Ala
Rashid, Ali Mahmud
Source
The Egyptian Journal of Language Engineering
Issue
Vol. 3, Issue 2 (30 Sep. 2016), pp.14-24, 11 p.
Publisher
Egyptian Society of Language Engineering
Publication Date
2016-09-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Sentiment analysis (also known as opinion mining) identifies and analyzes opinions and emotions in many domains (e.g.
news, articles, product reviews, blogs, forum posts).
Opinion mining is very important for companies, governments and every one interested to know opinion about special subject.
This research discusses the problem of identifying opinion in Arabic news and Arabic articles.
Most previous researches focused on extracting opinion from direct sentiments at the level of the article.
Considering that an article contains large number of sentences, and some of these sentences may be about different topics and may be not opinion sentence, we propose a new methodology for sentiment analysis for Arabic articles.
It starts with identifying opinion sentence related to the target of the article.
Machine learning and Typed Dependency Relations (TDR) are used to identify the opinion sentences.
Sentences that contain one word of high frequency nouns or adjectives are classified as target sentences.
Then opinion lexicon is built using machine learning based on dataset that was collected from different domains (e.g.
politics, economy, government, sports, and art).
Three methods are used to identify opinion mining in articles.
A method that depends on Opinion Lexicon achieved F-score of 62.8%.
Machine learning (SVM) method achieved F-score 42.63%.
whereas, our method that identifies opinion sentences that are related to the target of article then using opinion lexicon achieved the best results (F-score of 73.25%).
So we recommended to identify opinion sentences that are related to the target of the article, then use the opinion lexicon to know the opinion.
American Psychological Association (APA)
Farahat, Fawzia Zaki& Hamudah, Ala& Rashid, Ali Mahmud. 2016. Sentiment analysis system for Arabic articles news (SASAAN). The Egyptian Journal of Language Engineering،Vol. 3, no. 2, pp.14-24.
https://search.emarefa.net/detail/BIM-941689
Modern Language Association (MLA)
Farahat, Fawzia Zaki…[et al.]. Sentiment analysis system for Arabic articles news (SASAAN). The Egyptian Journal of Language Engineering Vol. 3, no. 2 (Sep. 2016), pp.14-24.
https://search.emarefa.net/detail/BIM-941689
American Medical Association (AMA)
Farahat, Fawzia Zaki& Hamudah, Ala& Rashid, Ali Mahmud. Sentiment analysis system for Arabic articles news (SASAAN). The Egyptian Journal of Language Engineering. 2016. Vol. 3, no. 2, pp.14-24.
https://search.emarefa.net/detail/BIM-941689
Data Type
Journal Articles
Language
English
Notes
Record ID
BIM-941689