Hunter Prey Optimization with Hybrid Deep Learning for Fake News Detection on Arabic Corpus  

作　　者：Hala J.Alshahrani Abdulkhaleq Q.A.Hassan Khaled Tarmissi Amal S.Mehanna Abdelwahed Motwakel Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki 

机构地区：[1]Department of Applied Linguistics,College of Languages,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [2]Department of English,College of Science and Arts at Mahayil,King Khalid University,Muhayil,63763,Saudi Arabia [3]Department of Computer Sciences,College of Computing and Information System,Umm Al-Qura University,Makkah,24211,Saudi Arabia [4]Department of Digital Media,Faculty of Computers and Information Technology,Future University in Egypt,New Cairo,11845,Egypt [5]Department of Computer and Self Development,Preparatory Year Deanship,Prince Sattam bin Abdulaziz University,AlKharj,Saudi Arabia [6]Department of Information System,College of Computer Engineering and Sciences,Prince Sattam bin Abdulaziz University,AlKharj,Saudi Arabia

出　　处：《Computers, Materials & Continua》2023年第5期4255-4272,共18页计算机、材料和连续体（英文）

基　　金：The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Small Groups Project under Grant Number(120/43);Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R281);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4331004DSR32).

摘　　要：Nowadays,the usage of socialmedia platforms is rapidly increasing,and rumours or false information are also rising,especially among Arab nations.This false information is harmful to society and individuals.Blocking and detecting the spread of fake news in Arabic becomes critical.Several artificial intelligence(AI)methods,including contemporary transformer techniques,BERT,were used to detect fake news.Thus,fake news in Arabic is identified by utilizing AI approaches.This article develops a new hunterprey optimization with hybrid deep learning-based fake news detection(HPOHDL-FND)model on the Arabic corpus.The HPOHDL-FND technique undergoes extensive data pre-processing steps to transform the input data into a useful format.Besides,the HPOHDL-FND technique utilizes long-term memory with a recurrent neural network(LSTM-RNN)model for fake news detection and classification.Finally,hunter prey optimization(HPO)algorithm is exploited for optimal modification of the hyperparameters related to the LSTM-RNN model.The performance validation of the HPOHDL-FND technique is tested using two Arabic datasets.The outcomes exemplified better performance over the other existing techniques with maximum accuracy of 96.57%and 93.53%on Covid19Fakes and satirical datasets,respectively.

关 键 词：Arabic corpus fake news detection deep learning hunter prey optimizer classification model 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]