Unraveling user perceptions and biases: A comparative study of ML and DL models for exploring twitter sentiments towards ChatGPT

MakaleAçık ErişimScopus SJRQ2

Özet

ChatGPT is a powerful chatbot that used to generate human-like text. Chat GPT, developed by OpenAI, can answer many questions honestly, like a personal teacher who knows almost everything. It can perform various tasks such as question and answer, solving mathematical equations, writing text, debugging, and translating between languages. Compared to traditional chatbots, ChatGPT has been adopted by many users since its introduction. Some users feel that ChatGPT will override most content creation professions. This study analyzed users’ feelings about ChatGPT by analyzing tweets shared about ChatGPT. For this purpose, a hybrid Deep Learning (DL) model was developed using Convolutional Neural Networks (CNN) and Bi- Long Short-Term Memory (Bi-LSTM) models. The study has been compared with a number of DL and Machine Learning algorithms, LSTM, Bi-LSTM, CNN, Gated Recurrent Unit, Random Forests and Support Vector Machines. The experimental outcomes demonstrated that, the FastText-trained CNN-Bi-LSTM model exceeded the other models in terms of accuracy, reaching 96.59%.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/1485Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.jer.2023.11.023Yayıncı resmi DOI adresi
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Atıflar
Scopus
18
WoS
11
OpenAlex
13
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorBaker, Mohammed Rashad
dc.contributor.authorUtku, Anil
dc.date.accessioned2026-10-28T14:54:15.540605102Z
dc.date.available2026-10-28T14:54:15.540605102Z
dc.date.issued2025
dc.description.abstractChatGPT is a powerful chatbot that used to generate human-like text. Chat GPT, developed by OpenAI, can answer many questions honestly, like a personal teacher who knows almost everything. It can perform various tasks such as question and answer, solving mathematical equations, writing text, debugging, and translating between languages. Compared to traditional chatbots, ChatGPT has been adopted by many users since its introduction. Some users feel that ChatGPT will override most content creation professions. This study analyzed users’ feelings about ChatGPT by analyzing tweets shared about ChatGPT. For this purpose, a hybrid Deep Learning (DL) model was developed using Convolutional Neural Networks (CNN) and Bi- Long Short-Term Memory (Bi-LSTM) models. The study has been compared with a number of DL and Machine Learning algorithms, LSTM, Bi-LSTM, CNN, Gated Recurrent Unit, Random Forests and Support Vector Machines. The experimental outcomes demonstrated that, the FastText-trained CNN-Bi-LSTM model exceeded the other models in terms of accuracy, reaching 96.59%.
dc.identifier.doi10.1016/j.jer.2023.11.023
dc.identifier.eissn2307-1885
dc.identifier.endpage1665
dc.identifier.issn2307-1877
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85186239043
dc.identifier.startpage1658
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/1485
dc.identifier.volume13
dc.identifier.wosWOS:001514365600039
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofJournal of Engineering Research (Kuwait)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBi-LSTM
dc.subjectChatGPT
dc.subjectCNN
dc.subjectDeep Learning
dc.subjectSentiment Analysis
dc.subject.classificationEngineering, Multidisciplinary
dc.subject.classificationEngineering
dc.titleUnraveling user perceptions and biases: A comparative study of ML and DL models for exploring twitter sentiments towards ChatGPT
dc.typeArticle
rdl.citation.openalex13
rdl.citation.scopus18
rdl.citation.wos11
rdl.oa.statusgold
rdl.oa.urlhttps://doi.org/10.1016/j.jer.2023.11.023
rdl.scopus.quartileQ2
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)