{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T18:18:15Z","timestamp":1776709095118,"version":"3.51.2"},"reference-count":78,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,8,25]],"date-time":"2023-08-25T00:00:00Z","timestamp":1692921600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European University of Atlantic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Chatbots are AI-powered programs designed to replicate human conversation. They are capable of performing a wide range of tasks, including answering questions, offering directions, controlling smart home thermostats, and playing music, among other functions. ChatGPT is a popular AI-based chatbot that generates meaningful responses to queries, aiding people in learning. While some individuals support ChatGPT, others view it as a disruptive tool in the field of education. Discussions about this tool can be found across different social media platforms. Analyzing the sentiment of such social media data, which comprises people\u2019s opinions, is crucial for assessing public sentiment regarding the success and shortcomings of such tools. This study performs a sentiment analysis and topic modeling on ChatGPT-based tweets. ChatGPT-based tweets are the author\u2019s extracted tweets from Twitter using ChatGPT hashtags, where users share their reviews and opinions about ChatGPT, providing a reference to the thoughts expressed by users in their tweets. The Latent Dirichlet Allocation (LDA) approach is employed to identify the most frequently discussed topics in relation to ChatGPT tweets. For the sentiment analysis, a deep transformer-based Bidirectional Encoder Representations from Transformers (BERT) model with three dense layers of neural networks is proposed. Additionally, machine and deep learning models with fine-tuned parameters are utilized for a comparative analysis. Experimental results demonstrate the superior performance of the proposed BERT model, achieving an accuracy of 96.49%.<\/jats:p>","DOI":"10.3390\/info14090474","type":"journal-article","created":{"date-parts":[[2023,8,25]],"date-time":"2023-08-25T08:42:20Z","timestamp":1692952940000},"page":"474","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Analyzing Sentiments Regarding ChatGPT Using Novel BERT: A Machine Learning Approach"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5385-5593","authenticated-orcid":false,"given":"Sudheesh","family":"R","sequence":"first","affiliation":[{"name":"Kodiyattu Veedu, Kollam, Valakom 691532, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5751-5528","authenticated-orcid":false,"given":"Muhammad","family":"Mujahid","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8403-1047","authenticated-orcid":false,"given":"Furqan","family":"Rustam","sequence":"additional","affiliation":[{"name":"School of Computer Science, University College Dublin, D04 V1W8 Dublin, Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7641-2835","authenticated-orcid":false,"given":"Rahman","family":"Shafique","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7466-0798","authenticated-orcid":false,"given":"Venkata","family":"Chunduri","sequence":"additional","affiliation":[{"name":"Indiana State University, Terre Haute, IN 47809, USA"}]},{"given":"M\u00f3nica Gracia","family":"Villar","sequence":"additional","affiliation":[{"name":"Faculty of Social Science and Humanities, Universidad Europea del Atl\u00e1ntico, Isabel Torres 21, 39011 Santander, Spain"},{"name":"Department of Project Management, Universidad Internacional Iberoamericana Arecibo, Puerto Rico, PR 00613, USA"},{"name":"Department of Extension, Universidade Internacional do Cuanza, Cuito EN250, Bi\u00e9, Angola"}]},{"given":"Juli\u00e9n Brito","family":"Ballester","sequence":"additional","affiliation":[{"name":"Faculty of Social Science and Humanities, Universidad Europea del Atl\u00e1ntico, Isabel Torres 21, 39011 Santander, Spain"},{"name":"Universidad Internacional Iberoamericana, Campeche 24560, Mexico"},{"name":"Universitaria Internacional de Colombia, Bogot\u00e1 11001, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3134-7720","authenticated-orcid":false,"given":"Isabel de la Torre","family":"Diez","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Communications and Telematics Engineering, Unviersity of Valladolid, Paseo de Bel\u00e9n, 15, 47011 Valladolid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-6496","authenticated-orcid":false,"given":"Imran","family":"Ashraf","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Meshram, S., Naik, N., Megha, V., More, T., and Kharche, S. 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