Polarity Classification of Arabic Sentiments-Reference-Cited by-同舟云学术

Polarity Classification of Arabic Sentiments

Published:2016-07 Issue:3 Volume:11 Page:32-49
ISSN:1554-1045
Container-title:International Journal of Information Technology and Web Engineering
language:en
Short-container-title:

Author:

Al-Kabi Mohammed N.¹,Wahsheh Heider A.²,Alsmadi Izzat M.³

Affiliation:

1. Information Technology Faculty, Zarqa University, Zarqa, Jordan

2. College of Computer Science, King Khaled University, Abha, Saudi Arabia

3. University of New Haven, West Haven, CT, USA

Abstract

Sentiment Analysis/Opinion Mining is associated with social media and usually aims to automatically identify the polarities of different points of views of the users of the social media about different aspects of life. The polarity of a sentiment reflects the point view of its author about a certain issue. This study aims to present a new method to identify the polarity of Arabic reviews and comments whether they are written in Modern Standard Arabic (MSA), or one of the Arabic Dialects, and/or include Emoticons. The proposed method is called Detection of Arabic Sentiment Analysis Polarity (DASAP). A modest dataset of Arabic comments, posts, and reviews is collected from Online social network websites (i.e. Facebook, Blogs, YouTube, and Twitter). This dataset is used to evaluate the effectiveness of the proposed method (DASAP). Receiver Operating Characteristic (ROC) prediction quality measurements are used to evaluate the effectiveness of DASAP based on the collected dataset.

Publisher

IGI Global

Subject

General Computer Science

Reference39 articles.

1. Abbasi, A., Chen, H., & Salem, A. (2008). Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums. ACM Trans. Inf. Syst., 26(3).

2. Abdul-Mageed, M., Diab, M. T., & Korayem, M. (2011). Subjectivity and sentiment analysis of modern standard Arabic. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (HLT '11), Stroudsburg, PA, USA (Vol. 2, pp. 587-591).

3. Abdul-Mageed, M., & Korayem, M. (2010). Automatic Identification of Subjectivity in Morphologically Rich Languages: The Case of Arabic. Proceedings of the 1st Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA), Lisbon (pp. 2-6).

4. SAMAR: Subjectivity and sentiment analysis for Arabic social media

5. Automatic Lexicon Construction for Arabic Sentiment Analysis

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