Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach
Author
Source
The International Arab Journal of Information Technology
Issue
Vol. 16, Issue 6 (30 Nov. 2019), pp.995-1002, 8 p.
Publisher
Publication Date
2019-11-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Arabic language and Literature
Topics
Abstract EN
Arab Internet users tend to use dialectical words to express how they feel about products, services, and places.
Although, dialects in Arabic derived from the formal Arabic language, it differs in several aspects.
In general, Arabic sentiment analysis recently attracted lots of researchers’ attention.
A considerable amount of research has been conducted in Modern Standard Arabic (MSA), but little work has focused on dialectal Arabic.
The presence of the dialect in the Arabic texts made Arabic sentiment analysis is a challenging issue, due to it usually does not follow specific rules in writing or speaking system.
In this paper, we implement a semi-supervised approach for sentiment polarity classification of dialectal reviews with the presence of Modern Standard Arabic (MSA).
We combined dialectal sentiment lexicon with four classifying learning algorithm to perform the polarity classification, namely Support Vector Machines (SVM), Naïve Bayes (NB), Random Forest, and K-Nearest Neighbor (K-NN).
To select the features with which the classifiers can perform the best, we used three feature evaluation methods, namely, Correlation-based Feature Selection, Principal Components Analysis, and SVM Feature Evaluation.
In the experiment, we applied the approach to a data set which was manually collected.
The experimental results show that the approach yielded the highest classification accuracy using SVM algorithm with 92.3 %.
American Psychological Association (APA)
al-Harbi, Umar A.. 2019. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology،Vol. 16, no. 6, pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
Modern Language Association (MLA)
al-Harbi, Umar A.. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology Vol. 16, no. 6 (Nov. 2019), pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
American Medical Association (AMA)
al-Harbi, Umar A.. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 6, pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1001-1002
Record ID
BIM-915142