{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T06:29:39Z","timestamp":1774074579063,"version":"3.50.1"},"reference-count":33,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T00:00:00Z","timestamp":1709942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2024,3,31]]},"abstract":"<jats:p>In the realm of ChatGPT's language capabilities, exploring Arabic Sentiment Analysis emerges as a crucial research focus. This study centers on ChatGPT, a popular machine learning model engaging in dialogues with users, garnering attention for its exceptional performance and widespread impact, particularly in the Arab world. The objective is to assess people's opinions about ChatGPT, categorizing them as positive or negative. Despite abundant research in English, there is a notable gap in Arabic studies. We assembled a dataset from X (formerly known as Twitter), comprising 2,247 tweets, classified by Arabic language specialists. Employing various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and Na\u00efve Bayes (NB), we implemented hyperparameter optimization techniques such as Bayesian optimization, Grid Search, and random search to select the best hyperparameters that contribute to achieving the best performance. Through training and testing, performance enhancements were observed with optimization algorithms. SVM exhibited superior performance, achieving 90% accuracy, 88% precision, 95% recall, and 91% F1 score with Grid Search. These findings contribute valuable insights into ChatGPT's impact in the Arab world, offering a comprehensive understanding of sentiment analysis through machine learning methodologies.<\/jats:p>","DOI":"10.1145\/3638285","type":"journal-article","created":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T11:26:07Z","timestamp":1705317967000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":28,"title":["Arabic Sentiment Analysis for ChatGPT Using Machine Learning Classification Algorithms: A Hyperparameter Optimization Technique"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3221-2773","authenticated-orcid":false,"given":"Ahmad","family":"Nasayreh","sequence":"first","affiliation":[{"name":"Department of Information Technology and Computer\u00a0Sciences, Yarmouk University, Irbid, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2523-7819","authenticated-orcid":false,"given":"Rabia Emhamed Al","family":"Mamlook","sequence":"additional","affiliation":[{"name":"Department of Business Administration, Trine University, Angola, IN, USA and Department of Industrial Engineering, University Zawia, Tripoli, Libya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8415-0572","authenticated-orcid":false,"given":"Ghassan","family":"Samara","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9797-2409","authenticated-orcid":false,"given":"Hasan","family":"Gharaibeh","sequence":"additional","affiliation":[{"name":"Department of Information Technology and Computer\u00a0Sciences, Yarmouk University, Irbid, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9486-3533","authenticated-orcid":false,"given":"Mohammad","family":"Aljaidi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7679-9467","authenticated-orcid":false,"given":"Dalia","family":"Alzu'bi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Concordia University, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0850-7722","authenticated-orcid":false,"given":"Essam","family":"Al-Daoud","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"additional","affiliation":[{"name":"Computer Science Department, Al al-Bayt University, Mafraq, Jordan; Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan; MEU Research Unit, Middle East University, Amman, Jordan; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon; School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia; School of Engineering and Technology, Sunway University Malaysia, Petaling Jaya, Malaysia; Applied Science..."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,3,9]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105353"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1334-8"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-019-0602-x"},{"key":"e_1_3_1_5_2","unstructured":"X. Zhai. 2023. Chatgpt and ai: The game changer for education. 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M. Alomari H. M. Elsherif and K. Shaalan. 2017. Arabic tweets sentimental analysis using machine learning. Lecture Notes in Computer Science. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics) Vol. 10350. Springer. 602\u2013610. DOI:10.1007\/978-3-319-60042-0_66","DOI":"10.1007\/978-3-319-60042-0_66"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAIS48893.2020.9096751"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2022.027311"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.56294\/dm202345"},{"key":"e_1_3_1_22_2","doi-asserted-by":"crossref","unstructured":"J. P. Munggaran A. A. Alhafidz M. Taqy D. Aprianti R. Agustini and M. Munawir. 2023. 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