Deer Hunting Optimization with Deep Learning Enabled Emotion Classification on English Twitter Data  

作　　者：Abdelwahed Motwakel Hala J.Alshahrani Jaber S.Alzahrani Ayman Yafoz Heba Mohsen Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki 

机构地区：[1]Department of Computer and Self Development,Preparatory Year Deanship,Prince Sattam bin Abdulaziz University,AlKharj,Saudi Arabia [2]Department of Applied Linguistics,College of Languages,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [3]Department of Industrial Engineering,College of Engineering at Alqunfudah,Umm Al-Qura University,Makkah,Saudi Arabia [4]Department of Information Systems,Faculty of Computing and Information Technology,King Abdulaziz University,Jeddah,Saudi Arabia [5]Department of Computer Science,Faculty of Computers and Information Technology,Future University in Egypt,New Cairo,11835,Egypt [6]Department of Information System,College of Computer Engineering and Sciences,Prince Sattam bin Abdulaziz University,AlKharj,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第12期2741-2757,共17页计算机系统科学与工程(英文)

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP2022R281);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia;Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4340237DSR61).

摘　　要：Currently,individuals use online social media,namely Facebook or Twitter,for sharing their thoughts and emotions.Detection of emotions on social networking sites’finds useful in several applications in social welfare,commerce,public health,and so on.Emotion is expressed in several means,like facial and speech expressions,gestures,and written text.Emotion recognition in a text document is a content-based classification problem that includes notions from deep learning(DL)and natural language processing(NLP)domains.This article proposes a Deer HuntingOptimizationwithDeep Belief Network Enabled Emotion Classification(DHODBN-EC)on English Twitter Data in this study.The presented DHODBN-EC model aims to examine the existence of distinct emotion classes in tweets.At the introductory level,the DHODBN-EC technique pre-processes the tweets at different levels.Besides,the word2vec feature extraction process is applied to generate the word embedding process.For emotion classification,the DHODBN-EC model utilizes the DBN model,which helps to determine distinct emotion class labels.Lastly,the DHO algorithm is leveraged for optimal hyperparameter adjustment of the DBN technique.An extensive range of experimental analyses can be executed to demonstrate the enhanced performance of the DHODBN-EC approach.A comprehensive comparison study exhibited the improvements of the DHODBN-EC model over other approaches with increased accuracy of 96.67%.

关 键 词：Deer hunting optimization deep belief network emotion classification Twitter data sentiment analysis english corpus 

分 类 号：H31[语言文字—英语]