Improving Arabic Sentiment Classification Using a Combined Approach

Authors

  • Belgacem Brahimi University of Bejaia, Department of Computer Science
  • Mohamed Touahria University of Setif, Department of Computer Science
  • Abdelkamel Tari University of Bejaia, Department of Computer Science

DOI:

https://doi.org/10.13053/cys-24-4-3154

Keywords:

Text mining, opinion mining, sentiment classification, supervised learning, review extraction, combined approach

Abstract

The aim of sentiment classification is to automatically extract and classify a textual review as expressing a positive or negative opinion. In this paper, we study the sentiment classification problem in the Arabic language. We propose a method that attempts to extract subjective parts of document reviews. In addition, a lexicon is used to find implicit opinions and sentiments in reviews. We combine the extracted opinions with the sentiment words returned by the lexical approach. Finally, a feature reduction technique is applied. To evaluate the proposed method, support vector machines (SVM) classifier is applied for the classification task. The results indicate that our proposed approach provides superior performance in terms of classification measures.

Author Biography

Belgacem Brahimi, University of Bejaia, Department of Computer Science

Department of Computer science

Downloads

Published

2020-12-02

Issue

Vol. 24 No. 4 (2020): 24(4)2020

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.