Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Hassan Najadat
Jordan University of Science & Technology
Computer Science & IT Electrical & Electronics Engineering

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Fake news detection for Arabic headlines-articles news data using deep learning Hassan Najadat; Mais Tawalbeh; Rasha Awawdeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3951-3959

Abstract

Fake news has become increasingly prevalent in recent years. The evolution of social websites has spurred the expansion of fake news causing it to a mixture with truthful information. English fake news detection had the largest share of studies, unlike Arabic fake news detection, which is still very limited. Fake news phenomenon has changed people and social perspectives through revolts in several Arab countries. False news results in the distortion of reality ignite chaos and stir public judgments. This paper provides an Arabic fake news detection approach using different deep learning models including long short-term memory and convolutional neural network based on article-headline pairs to differentiate if a news headline is in fact related or unrelated to the parallel news article. In this paper, a dataset created about the war in Syria and related to the Middle East political issues is utilized. The whole data comprises 422 claims and 3,042 articles. The models yield promising results.
A review of website evaluation using web diagnostic tools and data envelopment analysis Hassan Najadat; Amer Al-Badarneh; Sawsan Alodibat
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.1755

Abstract

This paper presents a review of the most recently published works of the use of data envelopment analysis (DEA) in the evaluation of websites of different fields such as healthcare, e-business, e-commerce, and e-government. The evaluation of websites is performed using web diagnostic tools (WDTs). Some studies have evaluated e-government websites using WDTs only, while others integrate them with data envelopment analysis. We summarize each study including the country that was conducted in, the size of data set, inputs to DEA, outputs from DEA, the approach used, the tools used, and the results obtained. It also covers whether there is a use of combination between DEA and data mining or machine learning approaches to classify the efficiency of these websites.
Co-Authors Amer Al-Badarneh Mais Tawalbeh Rasha Awawdeh Sawsan Alodibat