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Arabic Tweets Sentiment Analysis using Hybrid Approaches

by Manal Essam, Mohamed Elmenshawy, Hamdy M. Mousa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 36
Year of Publication: 2020
Authors: Manal Essam, Mohamed Elmenshawy, Hamdy M. Mousa
10.5120/ijca2020920929

Manal Essam, Mohamed Elmenshawy, Hamdy M. Mousa . Arabic Tweets Sentiment Analysis using Hybrid Approaches. International Journal of Computer Applications. 175, 36 ( Dec 2020), 43-49. DOI=10.5120/ijca2020920929

@article{ 10.5120/ijca2020920929,
author = { Manal Essam, Mohamed Elmenshawy, Hamdy M. Mousa },
title = { Arabic Tweets Sentiment Analysis using Hybrid Approaches },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 36 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 43-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number36/31688-2020920929/ },
doi = { 10.5120/ijca2020920929 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:28.433472+05:30
%A Manal Essam
%A Mohamed Elmenshawy
%A Hamdy M. Mousa
%T Arabic Tweets Sentiment Analysis using Hybrid Approaches
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 36
%P 43-49
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The unrestrained–access to social media makes people share their daily life; a Twitter platform allows its users to openly express and share their emotions about several issues in a predefined length. Thus, it becomes one of the most dominant networks in Arabic countries. Therefore, the Sentiment Analysis of Arabic tweets is a practical task of analyzing common sentiments and feelings. However, the existing resources regularly focus on the English language due to the shortage of Arabic Sentiment resources. In this paper, a new sentence-based sentiment analysis system had developed for Arabic tweets. Initially, the main sentiment classification approaches had applied for the sentence-level to obtain the most suitable one. As a result, the steps towards the construction of a new dataset had evaluated. The experiments show that the supervised approach is the most accurate one, especially with the absence of the Arabic dialects’ (informal) lexicons. Experiments comparisons achieve satisfactory results with high accuracy (78.08%) by supervised approach, Unsupervised gives acceptable accuracy (75%), and F-measure (74.1%) using a Hybrid classifier.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Arabic social media Twitter sentiment analysis Arabic sentiment analysis aspect-based sentiment analysis machine learning.

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