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291931

Arabic Tweets Spam Detection Based on Various Supervised Machine Learning and Deep Learning Classifiers

Article

Last updated: 28 Dec 2024

OverviewSimilar Items

Subjects

-

Tags

Computer Engineering

Abstract

 In this paper, different machine learning algorithms, ensemble algorithms,
and deep learning algorithms are applied to Arabic tweets to detect whether it
human-generated or not. The tweets are used twice as preprocessed and nonpreprocessed to measure the effectiveness of Arabic preprocessing in the
classification process. The data is also tokenized with various methods like unigram,
trigram, and Term Frequency–Inverse Document Frequency. The experiments
show that the support vector machine with the non-preprocessed tweets and
unigram tokenization has the best performance of 83.11% and a precision of 0.9516
while it predicts the spam or not in a relatively small time.

DOI

10.21608/msaeng.2023.291931

Keywords

Machine Learning, Ensemble, Deep learning, Arabic Tweets, Twitter spam

Authors

First Name

Shimaa I.

Last Name

Hassan

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt

Email

shaimaa.rizk@feng.bu.edu.eg

City

-

Orcid

-

First Name

Lamiaa

Last Name

Elrefaei

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt

Email

lamia.alrefaai@feng.bu.edu.eg

City

-

Orcid

-

First Name

Mina

Last Name

Andraws

MiddleName

Shoukrey

Affiliation

Engineering Department, Nuclear Research Centre, Egyptian Atomic Energy Authority, Cairo, Egypt

Email

m.andros56801@feng.bu.edu.eg

City

-

Orcid

-

Volume

2

Article Issue

2

Related Issue

40382

Issue Date

2023-03-01

Receive Date

2023-03-23

Publish Date

2023-03-01

Page Start

1,099

Page End

1,119

Print ISSN

2812-5339

Online ISSN

2812-4928

Article File

MSAENG_Volume 2_Issue 2_Pages 1099-1119.pdf

PDF . 649.2kB

Link

https://msaeng.journals.ekb.eg/article_291931.html

Detail API

https://msaeng.journals.ekb.eg/service?article_code=291931

Order

291,931

Type

Original Article

Type Code

2,183

Publication Type

Journal

Publication Title

MSA Engineering Journal

Publication Link

https://msaeng.journals.ekb.eg/

MainTitle

Arabic Tweets Spam Detection Based on Various Supervised Machine Learning and Deep Learning Classifiers

Details

Type

Article

Created At

28 Dec 2024