A Concept-based Sentiment Analysis Approach for Arabic

Ahmed Nasser; Hayri Sever

doi:10.34028/iajit

Article Details

A Concept-based Sentiment Analysis Approach for Arabic

Authors:

Ahmed Nasser | Hayri Sever

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.17 Issue 5, pp.96-106

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001389379

pISSN:

2309-4524

DOI:

10.34028/iajit

Keywords:

Abstract:

 Concept-Based Sentiment Analysis (CBSA) methods are considered to be more advanced and more accurate when it 
compared to ordinary Sentiment Analysis methods, because it has the ability of detecting the emotions that conveyed by multi-
word expressions concepts in language. This paper presented a CBSA system for Arabic language which utilizes both of 
machine learning approaches and concept-based sentiment lexicon. For extracting concepts from Arabic, a rule-based concept 
extraction algorithm called semantic parser is proposed. Different types of feature extraction and representation techniques 
are experimented among the building prosses of the sentiment analysis model for the presented Arabic CBSA system. A 
comprehensive and comparative experiments using different types of classification methods and classifier fusion models, 
together with different combinations of our proposed feature sets, are used to evaluate and test the presented CBSA system. 
The experiment results showed that the best performance for the sentiment analysis model is achieved by combined Support 
Vector Machine-Logistic Regression (SVM-LR) model where it obtained a F-score value of 93.23% using the Concept-Based-
Features+Lexicon-Based-Features+Word2vec-Features (CBF+LEX+W2V) features combinations.

Article Details

A Concept-based Sentiment Analysis Approach for Arabic

Authors:

Ahmed Nasser | Hayri Sever

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.17 Issue 5, pp.96-106

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001389379

pISSN:

2309-4524

DOI:

10.34028/iajit

Arabic Sentiment Analysis

Concept-based Sentiment Analysis

Machine Learning and Ensemble Learning

Issues

Article Details

A Concept-based Sentiment Analysis Approach for Arabic

Authors: Ahmed Nasser | Hayri Sever

Publisher: Zarqa University, Jordan

Journal: The International Arab Journal of Information Technology (IAJIT) Vol.17 Issue 5, pp.96-106

Document Type: Article

Publication Date: 1/2020

Document Language: English

Document ID (Org No.): 2001389379

pISSN: 2309-4524

DOI: 10.34028/iajit

Arabic Sentiment Analysis

Concept-based Sentiment Analysis

Machine Learning and Ensemble Learning

Issues

Authors:

Ahmed Nasser | Hayri Sever

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.17 Issue 5, pp.96-106

Document Type:

Article

Publication Date:

1/2020

Document Language:

English

Document ID (Org No.):

2001389379

pISSN:

2309-4524

DOI:

10.34028/iajit