Ethics in the Era of ChatGPT: A Bibliometric Analysis of the Transformative Trajectory of Emerging Trends in Artificial Intelligence in Academic Research
Restricted accessResearch articleFirst published online December, 2025
Ethics in the Era of ChatGPT: A Bibliometric Analysis of the Transformative Trajectory of Emerging Trends in Artificial Intelligence in Academic Research
Generative AI like ChatGPT is transforming education and research rapidly. This study focuses on ethical considerations surrounding ChatGPT in academic research through a comprehensive bibliometric analysis of 245 research articles published between 2019–2024, collected from the Scopus database. The study uncovers a substantial surge in publications with a steep increase from 2023, peaking in 2024. Notably, prominent nations such as the USA and the UK lead in publications, with significant contributions from other countries, including Australia and China. Additionally, countries such as the UK, Australia, and the USA are among the top three producers of scholarly articles on generative AI. The study revealed current trends in the adoption of AI in academic settings, emphasizing the growing importance of ethical concerns. These findings offer a foundation for scholars, educators, and decision-makers to contemplate ethical and responsible practices in the context of AI's expanding role in academia.
AbafeE. A.BahtaY. T.JordaanH. (2022). Exploring Biblioshiny for historical assessment of global research on sustainable use of water in agriculture. Sustainability, 14(17), 10651. MDPI. https://doi.org/10.3390/su141710651
2.
AbdullayevaA. (2019). Impact of artificial intelligence on agricultural, healthcare and logistics industries. Annals of Spiru Haret University.Economic Series, 19(2), 167–175. https://doi.org/10.26458/1929
3.
AburassS.Abu RummanM. (2024). Authenticity in authorship: The writer’s integrity framework for verifying human-generated text. Ethics and Information Technology, 26(3), 62. https://doi.org/10.1007/s10676-024-09797-z
4.
Al-kfairyM.MustafaD.KshetriN.InsiewM.AlfandiO. (2024). Ethical challenges and solutions of generative AI: An interdisciplinary perspective. Informatics, 11(3), 58. https://doi.org/10.3390/informatics11030058
5.
AliH.AysanA. F. (2025). Ethical dimensions of generative AI: A cross-domain analysis using machine learning structural topic modeling. International Journal of Ethics and Systems, 41(1), 3–34. https://doi.org/10.1108/IJOES-04-2024-0112
6.
AriaM.CuccurulloC. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
7.
BadwaikR. (2019). Artificial intelligence and machine learning: Changing paradigm in diagnostics and imaging. International Journal of Research in Medical Sciences, 8(1), 382. https://doi.org/10.18203/2320-6012.ijrms20195940
8.
BallardiniR. M.HeK.RoosT. (2019). AI-generated content: Authorship and inventorship in the age of artificial intelligence. In Online Distribution of Content in the EU (pp. 117–135). Edward Elgar Publishing. https://doi.org/10.4337/9781788119900.00015
9.
BaloğluG.ÇakaliK. R. (2023). Is artificial intelligence a new threat to the academic ethics?: Enron scandal revisited by ChatGPT. İşletme: The Business Journal, 4(1), 143–165. https://doi.org/isletme.1244633
10.
BaltaN. (2023). Ethical considerations in using AI in educational research. Journal of Research in Didactical Sciences, 2(1), 51–53. https://doi.org/10.51853/jorids/14204
11.
BenrimohD.IsraelS.PerlmanK.FratilaR.KrauseM. (2018). Meticulous transparency—an evaluation process for an agile AI regulatory scheme. In M. Mouhoub, S. Sadaoui, O. Ait Mohamed, & M. Ali (Eds.), Recent trends and future technology in applied intelligence. IEA/AIE 2018. Lecture Notes in Computer Science (Vol. 10868, pp. 869–880). Springer. https://doi.org/10.1007/978-3-319-92058-0_83
12.
BhullarP. S.JoshiM.ChughR. (2024). ChatGPT in higher education - a synthesis of the literature and a future research agenda. Education and Information Technologies, 29, 21501–21522. https://doi.org/10.1007/s10639-024-12723-x
13.
Bin-NashwanS. A.SadallahM.BouteraaM. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75, 1–11. https://doi.org/10.1016/j.techsoc.2023.102370
BontridderN.PoulletY. (2021). The role of artificial intelligence in disinformation. Data and Policy, 3, e32. https://doi.org/10.1017/dap.2021.20
16.
BordalejoB.PafumiD.OnuhF.KhalidA. K. M. I.PearceM. S.O’DonnellD. P. (2025). Scarlet cloak and the forest adventure”: A preliminary study of the impact of AI on commonly used writing tools. International Journal of Educational Technology in Higher Education, 22(1), 6. https://doi.org/10.1186/s41239-025-00505-5
17.
BoutadjineA.HarragF.ShaalanK. (2025). Human vs. Machine: A comparative study on the detection of AI-generated content. ACM Transactions on Asian and Low-Resource Language Information Processing, 24(2), 1–26. https://doi.org/10.1145/3708889
18.
BozkurtA. (2024). GenAI et al.: Cocreation, authorship, ownership, academic ethics and integrity in a time of generative AI. Open Praxis, 6(1), 1–10. https://doi.org/10.55982/openpraxis.16.1.654
19.
Chamorro-AtalayaO.Olivares-ZegarraS.Sobrino-ChungaL.Guerrero-CarranzaR.Vargas-DiazA.Huarcaya-GodoyM.Rasilla-RovegnoJ.Suarez-BazalarR.Poma-GarciaJ.Cruz-TeladaY. (2023). Application of the chatbot in university education: A bibliometric analysis of indexed scientific production in scopus, 2013-2023. International Journal of Learning, Teaching and Educational Research, 22(7), 281–304. https://doi.org/10.26803/ijlter.22.7.15
CohenM.KhavkinM.Movsowitz DavidowD.TochE. (2024). ChatGPT in the public eye: Ethical principles and generative concerns in social media discussions. New Media & Society. https://doi.org/10.1177/14614448241279034
DabisA.CsákiC. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanities and Social Sciences Communications, 11. https://doi.org/10.1057/s41599-024-03526-z
24.
DahlanM. A.OmarR.KamarudinS. (2024). ChatGPT in academia: A holistic examination of student performance and future implications. In HamdanA.HarrafA. (Eds.), Business development via AI and digitalization. Studies in systems, decision and control (Vol. 538, pp. 617–627). Springer. https://doi.org/10.1007/978-3-031-62102-4_51
25.
DanksD.LondonA. J. (2017). Algorithmic bias in autonomous systems. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, pp. 4691–4697. https://doi.org/10.24963/ijcai.2017/654
26.
DeltornJ.-M.MacrezF. (2018). Authorship in the age of machine learning and artificial intelligence. In S. M. O'Connor (Ed.), The Oxford handbook of music, law and policy. Oxford University Press, Centre for International Intellectual Property Studies (CEIPI) Research Paper No. 2018-10, 1–24. https://doi.org/10.2139/ssrn.3261329
27.
DeshpandeK. V.PanS.FouldsJ. R. (2020). Mitigating demographic bias in AI-based resume filtering. In UMAP 2020 Adjunct - Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, pp. 268–275. https://doi.org/10.1145/3386392.3399569
28.
DwivediY. K.KshetriN.HughesL.SladeE. L.JeyarajA.KarA. K.BaabdullahA. M.KoohangA.RaghavanV.AhujaM.AlbannaH.AlbashrawiM. A.Al-BusaidiA. S.BalakrishnanJ.BarletteY.BasuS.BoseI.BrooksL.BuhalisD.… WrightR. (2023). “So what if ChatGPT wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 1–63. https://doi.org/10.1016/j.ijinfomgt.2023.102642
29.
EkeD. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity?Journal of Responsible Technology, 13, 1–4. https://doi.org/10.1016/j.jrt.2023.100060
30.
EllegaardO.WallinJ. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?Scientometrics, 105(3), 1809–1831. https://doi.org/10.1007/s11192-015-1645-z
31.
FerraraE. (2023). Should ChatGPT be biased? Challenges and risks of bias in large language models. Computers and Society. https://doi.org/https://arxiv.org/abs/2304.03738
FonsecaB. P. F.SampaioR. B.FonsecaM. V. A.ZickerF. (2016). Co-authorship network analysis in health research: Method and potential use. Health Research Policy and Systems, 14. https://doi.org/10.1186/s12961-016-0104-5
34.
GlänzelW.SchubertA. (2019). Analysing scientific networks through co-authorship. In Handbook of quantitative science and technology research (pp. 257–276). Kluwer Academic Publishers. https://doi.org/10.1007/1-4020-2755-9_12
35.
GuleriaA.KrishanK.SharmaV.KanchanT. (2023). ChatGPT: Ethical concerns and challenges in academics and research. The Journal of Infection in Developing Countries, 17(9), 1292–1299. https://doi.org/10.3855/jidc.18738
36.
GulumbeB. H.AuduS. M.HashimA. M. (2025). Balancing AI and academic integrity: What are the positions of academic publishers and universities?AI and Society, 40, 1775–1784. https://doi.org/10.1007/s00146-024-01946-8
37.
HaltaufderheideJ.RanischR. (2024). The ethics of ChatGPT in medicine and healthcare: A systematic review on large language models (LLMs). npj Digital Medicine, 7, 183. https://doi.org/10.1038/s41746-024-01157-x
HappaJ.NurseJ. R. C.GoldsmithM.CreeseS.WilliamsR. (2018). An ethics framework for research into heterogeneous systems. Living in the Internet of Things: Cybersecurity of the IoT, 1–8. https://doi.org/10.1049/cp.2018.0026
40.
HuaS.JinS.JiangS. (2024). The limitations and ethical considerations of ChatGPT. Data Intelligence, 6(1), 201–239. https://doi.org/10.1162/dint_a_00243
41.
İriR.ÜnalE. (2024). Bibliometric analysis bibliometric analysis of research (1980-2023). Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 10(2), 386–403. https://doi.org/10.31592/aeusbed.1446738
42.
KavithaK.JoshithV. P. (2024). The transformative trajectory of artificial intelligence in education: The two decades of bibliometric retrospect. Journal of Educational Technology Systems, 52(3), 376–405. https://doi.org/10.1177/00472395241231815
43.
KesslerF. C.SlocumT. A. (2011). Analysis of thematic maps published in two geographical journals in the twentieth century. Annals of the Association of American Geographers, 101(2), 292–317. https://doi.org/10.1080/00045608.2010.544947
44.
KhalifaM.AlbadawyM. (2024). Using artificial intelligence in academic writing and research: an essential productivity tool. In Computer methods and programs in biomedicine update (Vol. 5, pp. 1–11). Elsevier B.V. https://doi.org/10.1016/j.cmpbup.2024.100145
45.
KhanN.KhanZ.KoubaaA.KhanM. K.SallehR. bin. (2024). Global insights and the impact of generative AI-ChatGPT on multidisciplinary: A systematic review and bibliometric analysis. Connection Science, 36(1). https://doi.org/10.1080/09540091.2024.2353630
46.
KimB. S.JoH. (2024). Why can’t artificial language contain the truth? A focus on Foucault’s and Heidegger’s discussions. Humanities and Social Sciences Communications, 11.https://doi.org/10.1057/s41599-024-03648-4
47.
KrepsS.MccainM.BrundageM. (2020). All the news that’s fit to fabricate: AI-generated text as a tool of media misinformation. Harvard Dataverse.https://doi.org/10.7910/DVN/1XVYU3
48.
LevyM.YehA.HawkesC.Lechner-ScottJ.GiovannoniG. (2023). Is using ChatGPT to help write papers and grants is useful, and ethical?Multiple Sclerosis and Related Disorders, 76, 104873. https://doi.org/10.1016/j.msard.2023.104873
49.
Leyrer-JacksonJ. M.WilsonA. K. (2018). The associations between social-media use and academic performance among undergraduate students in biology. Journal of Biological Education, 52(2), 221–230. https://doi.org/10.1080/00219266.2017.1307246
50.
LimW. M.KumarS.DonthuN. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, 1–31. https://doi.org/10.1016/j.jbusres.2024.114760
51.
MalhotraC.KotwalV.DalalS. (2018). Ethical framework for machine learning. 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K), 1–8. https://doi.org/10.23919/ITU-WT.2018.8597767
52.
MalikA. R.PratiwiY.AndajaniK.NumertayasaI. W.SuhartiS.DarwisA., & Marzuki. (2023). Exploring artificial intelligence in academic essay: Higher education student’s perspective. International Journal of Educational Research Open, 5, 1–11. https://doi.org/10.1016/j.ijedro.2023.100296
53.
MaphosaV.MaphosaM. (2023). Artificial intelligence in higher education: A bibliometric analysis and topic modeling approach. Applied Artificial Intelligence, 37(1). https://doi.org/10.1080/08839514.2023.2261730
MiaoJ.ThongprayoonC.SuppadungsukS.Garcia ValenciaO. A.QureshiF.CheungpasitpornW. (2024). Ethical dilemmas in using AI for academic writing and an example framework for peer review in nephrology academia: A narrative review. Clinics and Practice, 14(1), 89–105. https://doi.org/10.3390/clinpract14010008
56.
MongeonP.Paul-HusA. (2016). The journal coverage of web of science and scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5
57.
MumtazH.RiazM. H.WajidH.SaqibM.ZeeshanM. H.KhanS. E.ChauhanY. R.SohailH.VohraL. I. (2023). Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1203945
MuthukrishnanP. (2024). Prospective teachers’ AI literacy and responsible use of AI in assignment writing. Pakistan Journal of Life and Social Sciences, 22(2), 7245–7263. https://doi.org/10.57239/PJLSS-2024-22.2.00547
60.
NguyenA.HongY.DangB.HuangX. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 49(5), 847–864. https://doi.org/10.1080/03075079.2024.2323593
61.
NoyonsE. C. M.Calero-MedinaC. (2009). Applying bibliometric mapping in a high-level science policy context: Mapping the research areas of three Dutch universities of technology. Scientometrics, 79(2), 261–275. https://doi.org/10.1007/s11192-009-0417-z
62.
OberskiJ. E. J. (1988). Some statistical aspects of co-citation cluster analysis and a judgment by physicists. In Handbook of quantitative studies of science and technology (pp. 431–462). Elsevier. https://doi.org/10.1016/B978-0-444-70537-2.50019-2
63.
OkanovićP.OkanovićD.MitrovićD.MajstorovićN. (2013). Academic integrity “captured” by a personality-based test. Psihologija, 46(1), 61–75. https://doi.org/10.2298/PSI1301061O
64.
OwoseniA.KoladeO.EgbetokunA. (2024). Responsible use of generative AI for educators and students in higher education institutions. In Generative AI in higher education (pp. 151–172). Palgrave Macmillan. https://doi.org/10.1007/978-3-031-60179-8_6
65.
OyewolaD. O.DadaE. G. (2022). Exploring machine learning: A scientometrics approach using bibliometrix and VOSviewer. SN Applied Sciences, 4.https://doi.org/10.1007/s42452-022-05027-7
PerkinsM. (2023). Academic integrity considerations of AI large language models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching and Learning Practice, 20(2). https://doi.org/10.53761/1.20.02.07
QiuJ. P.DongK.YuH. Q. (2014). Comparative study on structure and correlation among author co-occurrence networks in bibliometrics. Scientometrics, 101(2), 1345–1360. https://doi.org/10.1007/s11192-014-1315-6
70.
QuY.WangJ. (2024). Performance and biases of large language models in public opinion simulation. Humanities and Social Sciences Communications, 11.https://doi.org/10.1057/s41599-024-03609-x
71.
RawatS.MeenaS. (2014). Publish or perish: Where are we heading?Journal of Research in Medical Sciences: The Official Journal of Isfahan University of Medical Sciences, 19(2), 87–89. https://pubmed.ncbi.nlm.nih.gov/24778659/
72.
RayP. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003
73.
RobinsonS.AlifantisT.EdwardsJ. S.LadbrookJ.WallerA. (2005). Knowledge-based improvement: Simulation and artificial intelligence for identifying and improving human decision-making in an operations system. Journal of the Operational Research Society, 56(8), 912–921. https://doi.org/10.1057/palgrave.jors.2601915
74.
SchmidtP.BiessmannF. (2020). Calibrating human-AI collaboration: Impact of risk, ambiguity and transparency on algorithmic bias. In HolzingerA.KiesebergP.TjoaA.WeipplE. (Eds.), Machine learning and knowledge extraction. CD-MAKE 2020. Lecture notes in computer science (Vol. 12279, pp. 431–449). Springer. https://doi.org/10.1007/978-3-030-57321-8_24
75.
SeptiawanR. (2024). Critical analysis of AI-produced media: A study of the implications of deepfake technology. Devotion: Journal of Research and Community Service, 5(7), 735–741. https://doi.org/10.59188/devotion.v5i7.747
76.
StahlB. C.EkeD. (2024). The ethics of ChatGPT – exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 1–14. https://doi.org/10.1016/j.ijinfomgt.2023.102700
77.
SullivanM.KellyA.McLaughlanP. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
78.
TliliA.ShehataB.AdarkwahM. A.BozkurtA.HickeyD. T.HuangR.AgyemangB. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10. https://doi.org/10.1186/s40561-023-00237-x
79.
TsengW.WarschauerM. (2023). AI-writing tools in education: If you can’t beat them, join them. Journal of China Computer-Assisted Language Learning, 3(2), 258–262. https://doi.org/10.1515/jccall-2023-0008
80.
WuX.DuanR.NiJ. (2024). Unveiling security, privacy, and ethical concerns of ChatGPT. Journal of Information and Intelligence, 2(2), 102–115. https://doi.org/10.1016/j.jiixd.2023.10.007
81.
YuH. (2024). The application and challenges of ChatGPT in educational transformation: New demands for teachers’ roles. Heliyon, 10(2), 1–15. https://doi.org/10.1016/j.heliyon.2024.e24289
82.
YuY.LiY.ZhangZ.GuZ.ZhongH.ZhaQ.YangL.ZhuC.ChenE. (2020). A bibliometric analysis using VOSviewer of publications on COVID-19. Annals of Translational Medicine, 8(13), 816–816. https://doi.org/10.21037/atm-20-4235
ZivcakovaL.WoodE. (2015). Examining instructional interventions: Encouraging academic integrity through active learning approaches. In LiM.ZhaoY. (Eds.), Exploring learning & teaching in higher education. New Frontiers of Educational Research (pp. 191–205). Springer. https://doi.org/10.1007/978-3-642-55352-3_8
