Navigating the social media market: AI and the challenge of fake news dissemination in the business environment
Abstract
Research background: Social media plays a crucial role today in enhancing or limiting how fake news is spread. Whether devised by man or developed by artificial intelligence, it has the power to rapidly change consumers’ minds, encouraging them to adopt new behaviors, perceive situations differently, or even act in total opposition to what might be expected. The new dynamics of communication highlights the need for an organizational response adapted to new AI technologies and to the dissemination of fake news within social media networks.
Purpose of this article: This paper aims to reveal, by means of bibliometric analysis and a systematic literature review, the generative capabilities of artificial intelligence in the creation and spread of fake news in the business environment, acknowledging the role of previous research in predicting accurately the constant developments in contemporary society.
Methods: The analysis is based on a PRISMA flowchart to examine how artificial intelligence technologies contribute to the creation of fake news whilst also highlighting potential artificial intelligence regulations and standards for limiting the dissemination of false information. Initially, the database included over 3,400 highly cited articles retrieved from Scopus and Web of Science, published in the last years, from which a total of 203 were selected for inclusion in the analysis. The bibliometric analysis follows research directions related to detection methods and strategies, legislation and policies governing artificial intelligence technologies used in the creation and dissemination of fake news connected to the business environment. Fake news typologies relating to the advancement of artificial intelligence new technologies are also explored.
Findings & value added: By analysing important phrases, including false information, misinformation, disinformation, mal-information, and deepfakes, this research investigates the categorization of fake news linked to the business environment and social media concepts. It underscores the need for better truth comprehension and the significance of fact-checking in preventing the spread of false information, with governance and institutional implications in terms of the economics of artificial intelligence-generated fake news in the social media market. While previous studies have examined the fake news phenomenon from several angles, there is still a research gap, as the literature concentrates more on how fake news is consumed rather than how it is created. This research aims to bridge the gap by providing a comprehensive examination of fake news research from the perspectives of fake news typology, creation, detection, and regulatory means.
Keywords
artificial intelligence (AI), fake news, social media, social media platforms, digital age, technology, systematic literature review, bibliometric analysis, stability of business environment, Web of Science
References
- Abbas, F., & Taeihagh, A. (2024). Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligence. Expert Systems with Applications, 252(Part B), 124260. DOI: https://doi.org/10.1016/j.eswa.2024.124260
View in Google Scholar - Ahmed, S., Hinkelmann, K., & Corradini, F. (2022a). Combining machine learning with knowledge engineering to detect fake news in social networks - A survey. arXiv preprint arXiv:2201.08032.
View in Google Scholar - Ahmed, I., Jeon, G., & Piccialli, F. (2022b). From artificial intelligence to explainable artificial intelligence in industry 4.0: A survey on what, how, and where. IEEE Transactions on Industrial Informatics, 18(8), 5031–5042. DOI: https://doi.org/10.1109/TII.2022.3146552
View in Google Scholar - Aïmeur, E., Amri, S., & Brassard, G. (2023). Fake news, disinformation and misinformation in social media: A review. Social Network Analysis and Mining, 13, 30. DOI: https://doi.org/10.1007/s13278-023-01028-5
View in Google Scholar - Akhtar, P., Ghouri, A. M., Khan, H. U. R., Amin, M., Awan, U., Zahoor, N., Khan, Z., & Ashraf, A. (2023). Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions. Annals of Operation Research, 327(2), 633–657. DOI: https://doi.org/10.1007/s10479-022-05015-5
View in Google Scholar - Ali, M., Gomes, L. M., Azab, N., Souza, J. G. D. M., Sorour, K., & Kimura, H. (2023). Panic buying and fake news in urban vs. rural UK: A case study of Twitter during COVID-19. Technological Forecasting and Social Change, 193, 122598. DOI: https://doi.org/10.1016/j.techfore.2023.122598
View in Google Scholar - Alghamdi, J., Suhuai L., & Lin, L. (2024). A comprehensive survey on machine learning approaches for fake news detection. Multimedia Tools and Applications, 83(17), 51009–51067. DOI: https://doi.org/10.1007/s11042-023-17470-8
View in Google Scholar - Al-Khassawneh, Y. A. (2023). A review of artificial intelligence in security and privacy: Research advances, applications, opportunities, and challenges. Indonesian Journal of Science and Technology, 8(1), 79–96. DOI: https://doi.org/10.17509/ijost.v8i1.52709
View in Google Scholar - Altheneyan, A., & Alhadlaq, A. (2023). Big data ML-based fake news detection using distributed learning. IEEE Access, 11, 29447–29463. DOI: https://doi.org/10.1109/ACCESS.2023.3260763
View in Google Scholar - Aprin, F., Peters, P., & Hoppe, H. U. (2023). The effectiveness of a virtual learning companion for supporting the critical judgment of social media content. Education and Information Technologies, 29, 12797–12830. DOI: https://doi.org/10.1007/s10639-023-12275-6
View in Google Scholar - Apuke, O. (2017). Quantitative research methods: A synopsis approach. Arabian Journal of Business and Management Review, 6, 40–47. DOI: https://doi.org/10.12816/0040336
View in Google Scholar - Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56, 101475. DOI: https://doi.org/10.1016/j.tele.2020.101475
View in Google Scholar - Assenmacher, C., Clever, L., Frischlich, L., Quandt, T., Trautmann, K., & Grimme, C. (2020). Demystifying social bots: On the intelligence of automated social media actors. Social Media + Society, 6(3), 1–14. DOI: https://doi.org/10.1177/2056305120939264
View in Google Scholar - Assenza, T., Collard, F., Fève, P., & Huber, S. J. (2024). From buzz to bust: How fake news shapes the business cycle. ECONtribute Policy Brief. University of Bonn and University of Cologne, Reinhard Selten Institute (RSI), 058.
View in Google Scholar - Baptista, J. P., & Gradim, A. (2020). Understanding fake news consumption: A review. Social Sciences, 9, 185. DOI: https://doi.org/10.3390/socsci9100185
View in Google Scholar - Beauvais, C. (2022). Fake news: Why do we believe it? Joint Bone Spine, 89(4), 105371. DOI: https://doi.org/10.1016/j.jbspin.2022.105371
View in Google Scholar - Biju, P. R., & Gayathri, O. (2023). Stop fake news: AI, algorithms and mitigation actions in India. Law, State & Telecommunications Review, 15(1), 207. DOI: https://doi.org/10.26512/lstr.v15i1.41873
View in Google Scholar - Broda, E., & Strömbäck, J. (2024). Misinformation, disinformation, and fake news: Lessons from an interdisciplinary, systematic literature review. Annals of the International Communication Association, 48(2), 139–166. DOI: https://doi.org/10.1080/23808985.2024.2323736
View in Google Scholar - Cham, T. H., Cheng, B. L., Aw, E. C. X., Tan, G. W. H., Loh, X. M., & Ooi, K. B. (2023). Counteracting the impact of online fake news on brands. Journal of Computer Information Systems, 64(2), 245–264. DOI: https://doi.org/10.1080/08874417.2023.2191350
View in Google Scholar - Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2023). Role of fake news and misinformation in supply chain disruption: Impact of technology competency as moderator. Annals of Operation Research, 327, 659–682. DOI: https://doi.org/10.1007/s10479-022-05001-x
View in Google Scholar - Chaudhuri, N., Gupta, G., & Popovič, A. (2025). Do you believe it? Examining user engagement with fake news on social media platforms. Technological Forecasting and Social Change, 212, 123950. DOI: https://doi.org/10.1016/j.techfore.2024.123950
View in Google Scholar - Choudhary, M., Jha, S., Prashant, Saxena, D., & Singh, A. K. (2021). A review of fake news detection methods using machine learning. In 2nd international conference for emerging technology (pp. 1–5). Danvers: IEEE Explore. DOI: https://doi.org/10.1109/INCET51464.2021.9456299
View in Google Scholar - Chung, K. C., Chen, C. H., Tsai, H. H., & Chuang, Y. H. (2021). Social media privacy management strategies: A SEM analysis of user privacy behaviors. Computer Communications, 174, 122–130. DOI: https://doi.org/10.1016/j.comcom.2021.04.012
View in Google Scholar - Comito, C., Caroprese, L., & Zumpano, E. (2023). Multimodal fake news detection on social media: A survey of deep learning techniques. Social Networking Analysis and Mining, 13, 101. DOI: https://doi.org/10.1007/s13278-023-01104-w
View in Google Scholar - Conroy, N. K., Rubin, V. L., & Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Sciences and Technology, 52, 1–4. DOI: https://doi.org/10.1002/pra2.2015.145052010082
View in Google Scholar - Costa, J. V. da, Bogea-Gomes, S., & Mira da Silva, M. (2024). Fake news: A conceptual model for risk management. Humanities and Social Sciences Communication, 11, 625. DOI: https://doi.org/10.1057/s41599-024-03096-0
View in Google Scholar - Cover, R., Haw, A., & Thompson, J. D. (2023). Remedying disinformation and fake news? The cultural frameworks of fake news crisis responses and solution-seeking. International Journal of Cultural Studies, 26(2), 216–233. DOI: https://doi.org/10.1177/13678779221136881
View in Google Scholar - Cummings, C. L., & Kong, W. Y. (2019). Breaking down “fake news”: Differences between misinformation, disinformation, rumors, and propaganda. In Resilience and hybrid threats (pp. 188–204). IOS Press.
View in Google Scholar - Cuteanu, C. O., & and Pop, C.-M. (2024). Fake news, a possible reason against consumers’ intentions to adopt new technology? Persuasion knowledge and its moderating effect. In Springer proceedings in business and economics (pp. 433–448). Cham: Springer. DOI: https://doi.org/10.1007/978-3-031-59858-6_29
View in Google Scholar - Damstra, A., Boomgaarden, H. G., Broda, E., Lindgren, E., Strömbäck, J., Tsfati, Y., & Vliegenthart, R. (2021). What does fake look like? A review of the literature on intentional deception in the news and on social media. Journalism Studies, 22(14), 1–17. DOI: https://doi.org/10.1080/1461670X.2021.1979423
View in Google Scholar - Datta, P., Whitmore, M., & Nwankpa, J. (2021). A perfect storm: Social media news, psychological biases, and AI. Digital Threats: Research and Practice, 2(2), 1–15. DOI: https://doi.org/10.1145/3428157
View in Google Scholar - de Ruiter, A. (2021). The distinct wrong of deepfakes. Philosophy & Technology, 34, 1311–1332. DOI: https://doi.org/10.1007/s13347-021-00459-2
View in Google Scholar - Dhall, S., Dwivedi, A. D., Pal, S. K., & Srivastava, G. (2021). Blockchain-based framework for reducing fake or vicious news spread on social media/messaging platforms. ACM Transactions on Asian and Low-Resource Language Information Processing, 21(1), 8. DOI: https://doi.org/10.1145/3467019
View in Google Scholar - Dong, Y., Willcott, N., Yang, X., & Yang, Y. (2025). Growing up in the modern world: How does artificial intelligence enhance firm growth? Managerial Finance. DOI: https://doi.org/10.1108/MF-09-2024-0715
View in Google Scholar - Dwivedi, V., & Sen, K. (2025). Navigating the challenges of fake news and media trust: A bibliometric study. Journal of Information, Communication and Ethics in Society. DOI: https://doi.org/10.1108/JICES-07-2024-0106
View in Google Scholar - Farhoudinia, B., Ozturkcan, S., & Kasap, N. (2023). Fake news in business and management literature: A systematic review of definitions, theories, methods and implications. Aslib Journal of Information Management. DOI: https://doi.org/10.1108/AJIM-09-2022-0418
View in Google Scholar - Fârte, G. I., Obada, D. R., Ghergut-Babii, A. N., & Dabija, D. C. (2025). Building corporate immunity: How do companies increase their resilience to negative information in the environment of fake news? Journal of Research in Interactive Marketing. DOI: https://doi.org/10.1108/JRIM-10-2024-0473
View in Google Scholar - Faruk, M., Rahman, M., & Shahedul, H. (2021). How digital marketing evolved over time: A bibliometric analysis on scopus database. Heliyon, 7(12), e08603. DOI: https://doi.org/10.1016/j.heliyon.2021.e08603
View in Google Scholar - Feuerriegel, S., DiResta, R., Goldstein, J. A., Kumar, S., Lorenz-Spreen, M., & Pröllochs, N. (2023). Research can help to tackle AI-generated disinformation. Nature Human Behaviour, 7, 1818–1821. DOI: https://doi.org/10.1038/s41562-023-01726-2
View in Google Scholar - Funke, D., & Flamini, D. (2019). A guide to anti-misinformation actions around the world. Poynter Institute.
View in Google Scholar - Fusco, F. (2022). Artificial intelligence and fake news: Criminal aspects in Pakistan and Saudi Arabia. Pakistan Journal of Criminology, 14(4), 19–33.
View in Google Scholar - Gambín, Á. F., Yazidi, A., Vasilakos, A., Haugerud, H., & Djenouri, Y. (2024). Deepfakes: Current and future trends. Artificial Intelligence Review, 57, 64. DOI: https://doi.org/10.1007/s10462-023-10679-x
View in Google Scholar - Gandía, J. A. G., Gavrila, S., de Lucas Ancillo, A., & del Val Núñez, M. T. (2025). Towards sustainable business in the automation era: Exploring its transformative impact from top management and employee perspective. Technological Forecasting and Social Change, 210, 123908. DOI: https://doi.org/10.1016/j.techfore.2024.123908
View in Google Scholar - García-Orosa, B. (2021). Disinformation, social media, bots, and astroturfing: The fourth wave of digital democracy. El Profesional de la Información, 30(6), e300603. DOI: https://doi.org/10.3145/epi.2021.nov.03
View in Google Scholar - Gaurav, A., Chui, K. T., Arya, V., Attar, R. W., Bansal, S., Alhomoud, A., & Psannis, K. (2024). Optimized AI-driven semantic web approach for enhancing phishing detection in e-commerce platforms. International Journal on Semantic Web and Information Systems (IJSWIS), 20(1), 1–13. DOI: https://doi.org/10.4018/IJSWIS.359767
View in Google Scholar - Ghobakhloo, M., Iranmanesh, M., Foroughi, B., Tseng, M. L., Nikbin, D., & Khanfar, A. A. (2025). Industry 4.0 digital transformation and opportunities for supply chain resilience: A comprehensive review and a strategic roadmap. Production Planning & Control, 36(1), 61–91. DOI: https://doi.org/10.1080/09537287.2023.2252376
View in Google Scholar - Giandomenico, Di D., Sit, J., Ishizaka, A., & Nunan, D. (2021). Fake news, social media and marketing: A systematic review. Journal of Business Research, 124, 329–341. DOI: https://doi.org/10.1016/j.jbusres.2020.11.037
View in Google Scholar - Gil de Zúñiga, H., & Kim, J.-N. (2025). Intervening troubled marketplace of ideas: How to redeem trust in media and social institutions from pseudo-information. American Behavioral Scientist, 69(2), 103–112. DOI: https://doi.org/10.1177/00027642221118279
View in Google Scholar - Golda, A., Mekonen, K., Pandey, A., Singh, A., Hassija, V., Chamola, V., & Sikdar. B. (2024). Privacy and security concerns in generative AI: A comprehensive survey. IEEE Access, 12, 1–1. DOI: https://doi.org/10.1109/ACCESS.2024.3381611
View in Google Scholar - Gongane, V. U., Munot, M. V., & Anuse, A. D. (2024). A survey of explainable AI techniques for detection of fake news and hate speech on social media platforms. Journal of Computational Social Science, 7, 587–623. DOI: https://doi.org/10.1007/s42001-024-00248-9
View in Google Scholar - Granstedt, A. (2024). The past, present, and future of social media marketing ethics. AMS Review, 14, 278–296. DOI: https://doi.org/10.1007/s13162-024-00294-6
View in Google Scholar - Gradon, K. (2023). Disinformation and artificial intelligence techniques: A double-edged sword? Retrieved from https://shorturl.at/1Xsjz (10.11.2024).
View in Google Scholar - Grewal, D., Satornino, C.B., Davenport, T., & Guha, A. (2024). How generative AI Is shaping the future of marketing. Journal of the Academy of Marketing Science. DOI: https://doi.org/10.1007/s11747-024-01064-3
View in Google Scholar - Guleria, A., Krishan, K., Sharma, V., & Kanchan, T. (2024). ChatGPT: Forensic, legal, and ethical issues. Medicine, Science and the Law, 64(2), 150–156. DOI: https://doi.org/10.1177/00258024231191829
View in Google Scholar - Gupta, A., Kumar, N., Prabhat, P., Gupta, R., Tanwar, S., Sharma, G., Bokoro, P. N., & Sharma, R. (2022). Combating fake news: Stakeholder interventions and potential solutions. IEEE Access, 10, 78268–78289. DOI: https://doi.org/10.1109/ACCESS.2022.3193670
View in Google Scholar - Gupta, M., Akiri, C., Aryal, K., Parker, E., & Praharaj, L. (2023). From ChatGPT to ThreatGPT: Impact of generative AI in cybersecurity and privacy. IEEE Access, 11, 80218–80245. DOI: https://doi.org/10.1109/ACCESS.2023.3300381
View in Google Scholar - Gurgun, S., Cemiloglu, D., Close, E. A., Phalp, K., Nakov, P., & Ali, R. (2024). Why do we not stand up to misinformation? Factors influencing the likelihood of challenging misinformation on social media and the role of demographics. Technology in Society, 76, 102444. DOI: https://doi.org/10.1016/j.techsoc.2023.102444
View in Google Scholar - Hashmi, E., Yamin, M. M., & Yayilgan, S.Y. (2024). Securing tomorrow: A comprehensive survey on the synergy of artificial intelligence and information security. AI and Ethics. DOI: https://doi.org/10.1007/s43681-024-00529-z
View in Google Scholar - Hu, B., Mao, Z., & Zhang, Y. (2025). An overview of fake news detection: From a new perspective. Fundamental Research, 5(1), 17. DOI: https://doi.org/10.1016/j.fmre.2024.01.017
View in Google Scholar - Hussain, M., & Soomro, T. (2023). Social media: An exploratory study of information, misinformation, disinformation, and malinformation. Applied Computer Systems, 28(1), 13–20. DOI: https://doi.org/10.2478/acss-2023-0002
View in Google Scholar - Iamandi, I. E., Constantin, L. G., Munteanu, S. M., & Cernat-Gruici, B. (2024). Insights on the relationship between artificial intelligence skills and national culture. Amfiteatru Economic, 26(67), 741–761. DOI: https://doi.org/10.24818/EA/2024/67/741
View in Google Scholar - Iqbal, A., Shahzad, K., Khan, S. A., & Chaudhry, M. S. (2023). The relationship of artificial intelligence (AI) with fake news detection (FND): A systematic literature review. Global Knowledge, Memory and Communication. DOI: https://doi.org/10.1108/GKMC-07-2023-0264
View in Google Scholar - Jayawardena, N. S., Quach, S., Thaichon, P., Ross, M., Weaven, S., & Behl, A. (2023). Organisational and regulatory strategies to combat false news circulation on social media. Journal of Strategic Marketing. DOI: https://doi.org/10.1080/0965254X.2023.2253815
View in Google Scholar - Juefei-Xu, F., Wang, R., Huang, Y., Guo, Q., Ma, L., & Liu, Y. (2021). Countering malicious deepfakes: Survey, battleground, and horizon. arXiv preprint. arXiv:2103.00218. DOI: https://doi.org/10.1007/s11263-022-01606-8
View in Google Scholar - Kaliyar, R. K., Goswami, A., Narang, P., & Chamola, V. (2022). Understanding the use and abuse of social media: Generalized fake news detection with a multichannel deep neural network. IEEE Transactions on Computational Social Systems, 11(4), 4878–4887. DOI: https://doi.org/10.1109/TCSS.2022.3221811
View in Google Scholar - Kane, T. B. (2019). Artificial intelligence in politics: Establishing ethics. IEEE Technology and Society Magazine, 38(1), 72–80. DOI: https://doi.org/10.1109/MTS.2019.2894474
View in Google Scholar - Karwa, R. R., & Gupta, S. R. (2022). Automated hybrid Deep Neural Network model for fake news identification and classification in social networks. Journal of Integrated Science & Technology, 10(2), 110–119.
View in Google Scholar - Kaur, K., & Gupta, S. (2023). Towards dissemination, detection and combating misinformation on social media: A literature review. Journal of Business & Industrial Marketing, 38(8), 1656–1674. DOI: https://doi.org/10.1108/JBIM-02-2022-0066
View in Google Scholar - Kausar, N., AliKhan, A., & Sattar, M. (2022). Towards better representation learning using hybrid deep learning model for fake news detection. Social Network Analysis and Mining, 12(1), 165. DOI: https://doi.org/10.1007/s13278-022-00986-6
View in Google Scholar - Kaushik, D. (2024). Policy responses to fake news on social media platforms: A law and economics analysis. Statute Law Review, 45(1), hmae013. DOI: https://doi.org/10.1093/slr/hmae013
View in Google Scholar - Kietzmann, J., Lee, L., McCarthy, I. P., & Kietzmann, T. (2020). Deepfakes: Trick or treat? Business Horizons, 63(2), 135–146. DOI: https://doi.org/10.1016/j.bushor.2019.11.006
View in Google Scholar - Kim, B., Xiong, A., Lee, D., & Han, K. (2021). A systematic review on fake news research through the lens of news creation and consumption: Research efforts, challenges, and future directions. Plos One, 16(12), e0260080. DOI: https://doi.org/10.1371/journal.pone.0260080
View in Google Scholar - Kouroutakis, A. (2024). Rule of law in the AI era: Addressing accountability, and the digital divide. Discover Artificial Intelligence, 4(1), 115. DOI: https://doi.org/10.1007/s44163-024-00191-8
View in Google Scholar - Kožuh, I., & Čakš, P. (2023). Social media fact-checking: The effects of news literacy and news trust on the intent to verify health-related information. Healthcare, 11, 2796. DOI: https://doi.org/10.3390/healthcare11202796
View in Google Scholar - Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020). Citizens versus the Internet: Confronting digital challenges with cognitive tools. Psychological Science in the Public Interest, 21(3), 103–156. DOI: https://doi.org/10.1177/1529100620946707
View in Google Scholar - Krizanova, A., Lăzăroiu, G., Gajanova, L., Kliestikova, J., Nadanyiova, M., & Moravcikova, D. (2019). The effectiveness of marketing communication and importance of its evaluation in an online environment. Sustainability, 11(24), 7016. DOI: https://doi.org/10.3390/su11247016
View in Google Scholar - Lan, D. H., & Tung, T. M. (2024). Exploring fake news awareness and trust in the age of social media among university student TikTok users. Cogent Social Sciences, 10(1), 1–24. DOI: https://doi.org/10.1080/23311886.2024.2302216
View in Google Scholar - Lăzăroiu, G. (2017). The routine fabric of understandable and contemptible lies. Educational Philosophy and Theory, 49(6), 573–574. DOI: https://doi.org/10.1080/00131857.2017.1288791
View in Google Scholar - Lăzăroiu, G., Pera, A., Ştefănescu-Mihăilă, R. O., Bratu, S., & Mircică, N. (2017a). The cognitive information effect of televised news. Frontiers in Psychology, 8, 1165. DOI: https://doi.org/10.3389/fpsyg.2017.01165
View in Google Scholar - Lăzăroiu, G., Pera, A., Ștefănescu-Mihăilă, R. O., Mircică, N., & Neguriță, O. (2017b). Can neuroscience assist us in constructing better patterns of economic decision-making? Frontiers in Behavioral Neuroscience, 11, 188. DOI: https://doi.org/10.3389/fnbeh.2017.00188
View in Google Scholar - Lewandowsky, S., Ecker, U. K., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131. DOI: https://doi.org/10.1177/1529100612451018
View in Google Scholar - Li, B., Ju, J., Wang, C., & Pan, S. (2023). How does ChatGPT affect fake news detection systems? In X. Yang, H. Suhartanto, G. Wang, B. Wang, J. Jiang, B. Li, H. Zhu & N. Cui (Eds.). Advanced data mining and applications. Lecture notes in computer science. 19th international conference ADMA 2023 (pp. 565–580). Cham: Springer. DOI: https://doi.org/10.1007/978-3-031-46664-9_38
View in Google Scholar - Lim, W. M. (2023). Fact or fake? The search for truth in an infodemic of disinformation, misinformation, and malinformation with deepfake and fake news. Journal of Strategic Marketing. DOI: https://doi.org/10.1080/0965254X.2023.2253805
View in Google Scholar - Lim, X. J., Quach, S., Thaichon, P., Cheah, J. H., & Ting, H. (2024). Fact or fake: Information, misinformation and disinformation via social media. Journal of Strategic Marketing, 32(5), 659–664. DOI: https://doi.org/10.1080/0965254X.2024.2306558
View in Google Scholar - Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2020). Conducting systematic literature reviews and bibliometric analyses. Australian Journal of Management, 45(2), 175–194. DOI: https://doi.org/10.1177/0312896219877678
View in Google Scholar - Ma, H. V., Huang, W., & Dennis, A. R. (2024). Unintended consequences of disclosing recommendations by artificial intelligence versus humans on true and fake news believability and engagement. Journal of Management Information Systems, 41(3), 616–644. DOI: https://doi.org/10.1080/07421222.2024.2376381
View in Google Scholar - Macarrón-Máñez, M. T., Moreno Cano, A., & Díez, F. (2024). Impact of fake news on social networks during COVID-19 pandemic in Spain. Young Consumers, 25(4), 439–461. DOI: https://doi.org/10.1108/YC-04-2022-1514
View in Google Scholar - Marsden, C., Meyer, T., & Brown, I. (2020). Platform values and democratic elections: How can the law regulate digital disinformation? Computer Law and Security Review, 36, 105373. DOI: https://doi.org/10.1016/j.clsr.2019.105373
View in Google Scholar - Meel, P., & Vishwakarma, D. K. (2021). A temporal ensembling based semi-supervised ConvNet for the detection of fake news articles. Expert Systems with Applications, 177, 115002. DOI: https://doi.org/10.1016/j.eswa.2021.115002
View in Google Scholar - Montoro-Montarroso, A., Cantón-Correa, J., Rosso, P., Chulvi, B., Panizo-Lledot, Á., Huertas-Tato, J., Calvo-Figueras, B., Rementeria, M., & Gómez-Romero, J. (2023). Fighting disinformation with artificial intelligence: Fundamentals, advances and challenges. El Profesional de la Información, 32(3), 1–16. DOI: https://doi.org/10.3145/epi.2023.may.22
View in Google Scholar - Muñoz, S., & Iglesias, C. Á. (2024). Exploiting content characteristics for explainable detection of fake news. Big Data Cognition and Computing, 8, 129. DOI: https://doi.org/10.3390/bdcc8100129
View in Google Scholar - Nam, J., Jung, Y., & Kim, J. (2024). Understandings of the AI business ecosystem in South Korea: AI startups’ perspective. Telecommunications Policy, 48(6), 102763. DOI: https://doi.org/10.1016/j.telpol.2024.102763
View in Google Scholar - Nasery, M., Turel, O., & Yuan, Y. (2023). Combating fake news on social media: A framework, review, and future opportunities. Communications of the Association for Information Systems, 53, 833–876. DOI: https://doi.org/10.17705/1CAIS.05335
View in Google Scholar - Nasir, J. A., Khan, O. S., & Varlamis, I. (2021). Fake news detection: A hybrid CNN-RNN based deep learning approach. International Journal of Information Management Data Insights, 1(1), 100007. DOI: https://doi.org/10.1016/j.jjimei.2020.100007
View in Google Scholar - Obadă, D. R., & Dabija, D. C. (2022a). The mediation effects of social media usage and sharing fake news about companies. Behavioral Sciences, 12(10), 372. DOI: https://doi.org/10.3390/bs12100372
View in Google Scholar - Obadă, D. R., & Dabija, D. C. (2022b). “In flow”! Why do social-media users share fake news about environmentally friendly brands on social media? International Journal of Environmental Research and Public Health, 19(8), 4861. DOI: https://doi.org/10.3390/ijerph19084861
View in Google Scholar - Obada, D. R., Dabija, D. C., & Câmpian, V. (2024). Predictors of social media users’ intention to donate online toward international NGOs in the fake news era. Humanities & Social Sciences Communications, 11, 379. DOI: https://doi.org/10.1057/s41599-024-02900-1
View in Google Scholar - Olan, F., Jayawickrama, U., Arakpogun, E. O., Suklan, J., & Liu, S. (2024). Fake news on social media: The impact on society. Information Systems Frontiers, 26, 443–458. DOI: https://doi.org/10.1007/s10796-022-10242-z
View in Google Scholar - Omar, B., Apuke, O. D., & Nor, Z. M. (2024). The intrinsic and extrinsic factors predicting fake news sharing among social media users: The moderating role of fake news awareness. Current Psychology, 43, 1235–1247. DOI: https://doi.org/10.1007/s12144-023-04343-4
View in Google Scholar - Ozbay, F. A., & Alatas, B. (2020). Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Statistical Mechanics and its Applications, 540, 123174. DOI: https://doi.org/10.1016/j.physa.2019.123174
View in Google Scholar - Papageorgiou, E., Chronis, C., Varlamis, I., & Himeur, Y. (2024). A survey on the use of large language models (LLMs) in fake news. Future Internet, 16, 298. DOI: https://doi.org/10.3390/fi16080298
View in Google Scholar - Park, S., Fisher, C., Flew, T., & Dulleck, U. (2020). Global mistrust in news: The impact of social media on trust. International Journal on Media Management, 22(2), 83–96. DOI: https://doi.org/10.1080/14241277.2020.1799794
View in Google Scholar - Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 116(7), 2521–2526. DOI: https://doi.org/10.1073/pnas.1806781116
View in Google Scholar - Pennycook, G., Bear, A., Collins, E. T., & Rand, D. G. (2020). The implied truth effect: Attaching warnings to a subset of fake news headlines increases perceived accuracy of headlines without warnings. Management Science, 66(11), 4944–4957. DOI: https://doi.org/10.1287/mnsc.2019.3478
View in Google Scholar - Pennycook, G., Epstein, Z., Mosleh, M., Arechar, A. A., Eckles, D., & Rand, D. G. (2021). Shifting attention to accuracy can reduce misinformation online. Nature, 592, 590–595. DOI: https://doi.org/10.1038/s41586-021-03344-2
View in Google Scholar - Pérez-Dasilva, J., Meso Ayerdi, K., & Mendiguren Galdospin, T. (2021). Deepfakes on Twitter: Which actors control their spread? Media and Communication, 9(1), 301–312. DOI: https://doi.org/10.17645/mac.v9i1.3433
View in Google Scholar - Peters, M. A., Jackson, L., Papastephanou, M., Jandrić, P., Lazaroiu, G., Evers, C. W., Cope, B., Kalantzis, M., Araya, D., Tesar, M., Mika, C., Chen, L., Wang, C., Sturm, S., Rider, S., & Fuller, S. (2023). AI and the future of humanity: ChatGPT-4, philosophy and education – Critical responses. Educational Philosophy and Theory, 56(9), 828–862. DOI: https://doi.org/10.1080/00131857.2023.2213437
View in Google Scholar - Petratos, P. N. (2021). Misinformation, disinformation, and fake news: Cyber risks to business. Business Horizons, 64(6), 763–774. DOI: https://doi.org/10.1016/j.bushor.2021.07.012
View in Google Scholar - Petratos, P. N., & Faccia, A. (2023). Fake news, misinformation, disinformation and supply chain risks and disruptions: Risk management and resilience using blockchain. Annals of Operations Research, 327, 735–762. DOI: https://doi.org/10.1007/s10479-023-05242-4
View in Google Scholar - Pourghomi, P., Dordevic, M., & Safieddine, F. (2020). Facebook fake profile identification: technical and ethical considerations. International Journal of Pervasive Computing and Communications, 16(1), 101–112. DOI: https://doi.org/10.1108/IJPCC-06-2019-0049
View in Google Scholar - Raman, R., Nair, V. K., Nedungadi, P., Sahu, A. K., Kowalski, R., Ramanathan, S., & Achuthan, K. (2024). Fake news research trends, linkages to generative artificial intelligence and sustainable development goals. Heliyon, 10(3), e24727. DOI: https://doi.org/10.1016/j.heliyon.2024.e24727
View in Google Scholar - Rao, A. (2022). Deceptive claims using fake news advertising: The impact on consumers. Journal of Marketing Research, 59(3), 534–554. DOI: https://doi.org/10.1177/00222437211039804
View in Google Scholar - Rashidi-Sabet, S., & Bolton, D. E. (2024). Commitment-trust theory in social media interactions: Implications for firms. Journal of Marketing Management, 40(13–14), 1300–1335. DOI: https://doi.org/10.1080/0267257X.2024.2434143
View in Google Scholar - Rizvanović, B., Zutshi, A., Grilo, A., & Nodehi, T. (2023). Linking the potentials of extended digital marketing impact and start-up growth: Developing a macro-dynamic framework of start-up growth drivers supported by digital marketing. Technological Forecasting and Social Change, 186, 122128. DOI: https://doi.org/10.1016/j.techfore.2022.122128
View in Google Scholar - Sadiq, S., Kaiwei, J., Aman, I., & Mansab, M. (2025). Examine the factors influencing the behavioral intention to use social commerce adoption and the role of AI in SC adoption. European Research on Management and Business Economics, 31, 100268. DOI: https://doi.org/10.1016/j.iedeen.2024.100268
View in Google Scholar - Saheb, T., Sidaoui, M., & Schmarzo, B. (2024). Convergence of artificial intelligence with social media: A bibliometric & qualitative analysis. Telematics and Informatics Reports, 14, 100146. DOI: https://doi.org/10.1016/j.teler.2024.100146
View in Google Scholar - Sakshi, A., Mehrotra, T., Tyagi, P., & Jain, V. (2024). Emerging trends in hybrid information systems modeling in artificial intelligence. In R. Bhardwaj, P. Dutta, P. Raj, A. Kumar, K. Saini, A. González Briones, & M. Kaabar (Eds.). Hybrid information systems: Non-linear optimization strategies with artificial intelligence (pp. 115–152). Berlin, Boston: De Gruyter. DOI: https://doi.org/10.1515/9783111331133-007
View in Google Scholar - Sandu, A., Ioanăș, I., Delcea, C., Florescu, M.-S., & Cotfas, L.-A. (2024). Numbers do not lie: A bibliometric examination of machine learning techniques in fake news research. Algorithms, 17, 70. DOI: https://doi.org/10.3390/a17020070
View in Google Scholar - Santos, F. C. C. (2023). Artificial intelligence in automated detection of disinformation: A thematic analysis. Journalism and Media, 4, 679–687. DOI: https://doi.org/10.3390/journalmedia4020043
View in Google Scholar - Sardarizadeh, S. (2019). Instagram fact-check: Can a new flagging tool stop fake news? Retrieved from https://bbc.in/33fg5ZR (10.11.2024).
View in Google Scholar - Sedik, A, Abohany, A. A., Sallam, K. M., Munasinghe, K., & Medhat, T. (2022). Deep fake news detection system based on concatenated and recurrent modalities. Expert Systems with Applications, 208, 117953. DOI: https://doi.org/10.1016/j.eswa.2022.117953
View in Google Scholar - Shao, C., Hui, P.-M., Wang, L., Jiang, X., Flammini, A., & Menczer, F. (2018). Anatomy of an online misinformation network. Plos One, 13(4), e0196087. DOI: https://doi.org/10.1371/journal.pone.0196087
View in Google Scholar - Sharma, I., Jain, K., Behl, A., Baabdullah, A. M., Giannakis, M., & Dwivedi, Y. K. (2023). Examining the motivations of sharing political deepfake videos: The role of political brand hate and moral consciousness. Internet Research, 33, 1727–1749. DOI: https://doi.org/10.1108/INTR-07-2022-0563
View in Google Scholar - Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., & Liu, Y. (2019). Combating fake news: A survey on identification and mitigation techniques. ACM Transactions on Intelligent Systems and Technology, 10(3), 1–42. DOI: https://doi.org/10.1145/3305260
View in Google Scholar - Shim, J. S., Lee, Y., & Ahn, H. (2021). A link2vec-based fake news detection model using web search results. Expert Systems with Applications, 184, 115491. DOI: https://doi.org/10.1016/j.eswa.2021.115491
View in Google Scholar - Singh, M. K., Ahmed, J., Alam, M. A., Raghuvanshi, K. K., & Kumar, S. (2024). A comprehensive review on automatic detection of fake news on social media. Multimedia Tools and Applications, 83, 47319–47352. DOI: https://doi.org/10.1007/s11042-023-17377-4
View in Google Scholar - Stachofsky, J., Schaupp, L. C., & Crossler, R. E. (2023). Measuring the effect of political alignment, platforms, and fake news consumption on voter concern for election processes. Government Information Quarterly, 40(3), 101810. DOI: https://doi.org/10.1016/j.giq.2023.101810
View in Google Scholar - Stanescu, G. C. (2024). Fake news, bots, and influencers: The impact of social media on Romania’s 2024 elections. Social Sciences and Education Research Review, 11(2), 361–366.
View in Google Scholar - Suanpang, P., Pothipasa, P., & Netwrong, T. (2021). Policies and platforms for fake news filtering on cybercrime in smart city using artificial intelligence and blockchain technology. International Journal of Cyber Criminology, 15(1), 143–157.
View in Google Scholar - Suarez-Lledo, V., Ortega-Martin, E., Carretero-Bravo, J., Ramos-Fiol, B., & Alvarez-Galvez, J. (2025). Unraveling the use of disinformation hashtags by social bots during the COVID-19 pandemic: Social networks analysis. JMIR Infodemiology, 5, e50021. DOI: https://doi.org/10.2196/50021
View in Google Scholar - Tomassi, A., Falegnami, A., & Romano, E. (2024). Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society. PLoS One, 19(5), e0303183. DOI: https://doi.org/10.1371/journal.pone.0303183
View in Google Scholar - Tsfati, Y., Boomgaarden, H. G., Strömbäck, J., Vliegenthart, R., Damstra, A., & Lindgren, E. (2020). Causes and consequences of mainstream media dissemination of fake news: Literature review and synthesis. Annals of the International Communication Association, 44(2), 157–173. DOI: https://doi.org/10.1080/23808985.2020.1759443
View in Google Scholar - Tumasjan, A. (2024). The many faces of social media in business and economics research: Taking stock of the literature and looking into the future. Journal of Economic Surveys, 38(2), 389–426. DOI: https://doi.org/10.1111/joes.12570
View in Google Scholar - Ubillús, J. A. T., Ladera-Castañeda, M., Pacherres, C. A. A., Pacherres, M., Ángel, A., & Saavedra, C. L. I. (2023). Artificial intelligence to reduce misleading publications on social networks. EAI Endorsed Transactions on Scalable Information Systems, 10(6), 1–17. DOI: https://doi.org/10.4108/eetsis.3894
View in Google Scholar - Vaccari, C., & Chadwick, A. (2020). Deepfakes and disinformation: Exploring the impact of synthetic political video on deception, uncertainty, and trust in news. Social Media + Society, 6(1), 2056305120903408. DOI: https://doi.org/10.1177/2056305120903408
View in Google Scholar - Varma, R., Verma, Y., Vijayvargiya, P., & Churi, P. P. (2021). A systematic survey on deep learning and machine learning approaches of fake news detection in the pre-and post-COVID-19 pandemic. International Journal of Intelligent Computing and Cybernetics, 14(4), 617–646. DOI: https://doi.org/10.1108/IJICC-04-2021-0069
View in Google Scholar - Vasist, P. N., & Krishnan, S. (2025). Navigating the ethical terrain around the challenges of fake news and false narratives: An integrative literature review and a proposed agenda for future research. Journal of Business Ethics, 196, 473–493. DOI: https://doi.org/10.1007/s10551-024-05686-z
View in Google Scholar - Vecchietti, G., Liyanaarachchi, G., & Viglia, G. (2025). Managing deepfakes with artificial intelligence: Introducing the business privacy calculus. Journal of Business Research, 186, 115010. DOI: https://doi.org/10.1016/j.jbusres.2024.115010
View in Google Scholar - Vermeer, S., Trilling, D., Kruikemeier, S., & de Vreese, C. (2020). Online news user journeys: The role of social media, news websites, and topics. Digital Journalism, 8(9), 1114–1141. DOI: https://doi.org/10.1080/21670811.2020.1767509
View in Google Scholar - Verrall, N. (2022). COVID-19 disinformation, misinformation and malinformation during the pandemic infodemic: A view from the United Kingdom. In COVID-19 disinformation: A multi-national, whole of society perspective (pp. 81-112). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-94825-2_4
View in Google Scholar - Vicari, R., & Komendatova, N. (2023). Systematic meta-analysis of research on AI tools to deal with misinformation on social media during natural and anthropogenic hazards and disasters. Humanities and Social Sciences Communication, 10, 332. DOI: https://doi.org/10.1057/s41599-023-01838-0
View in Google Scholar - Vizoso, Á., Vaz-Álvarez, M., & García, X. (2021). Fighting deepfakes: Media and Internet giants' converging and diverging strategies against hi-tech misinformation. Media and Communication, 9(1), 291–300. DOI: https://doi.org/10.17645/mac.v9i1.3494
View in Google Scholar - Wang, S. T., Pang, M. S., & Pavlou, P. A. (2022). Seeing is believing? How including a video in fake news influences users' reporting of fake news to social media platforms. MIS Quarterly, 46(3), 1323–1354. DOI: https://doi.org/10.25300/MISQ/2022/16296
View in Google Scholar - Wei, X., Zhang, Z., Zhang, M. Y., Chen, W. Y., & Zeng, D. D. (2022). Combining crowd and machine intelligence to detect false news on social media. MIS Quarterly, 46(2), 977–1008. DOI: https://doi.org/10.25300/MISQ/2022/16256
View in Google Scholar - Weiss, A. P., Alwan, A., Garcia, E. P., & Kirakosian, A. T. (2021). Toward a comprehensive model of fake news: A new approach to examine the creation and sharing of false information. Societies, 11, 82. DOI: https://doi.org/10.3390/soc11030082
View in Google Scholar - Westerlund, M. (2019). The emergence of deepfake technology: A review. Technology Innovation Management Review, 9(11), 39–52. DOI: https://doi.org/10.22215/timreview/1282
View in Google Scholar - Williams, R. T. (2024). The ethical implications of using generative chatbots in higher education. Frontiers in Education, 8, 1331607. DOI: https://doi.org/10.3389/feduc.2023.1331607
View in Google Scholar - Wu, Y., Ngai, E. W. T., Wu, P., & Wu, C. (2022). Fake news on the internet: A literature review, synthesis and directions for future research. Internet Research, 32(5), 1662–1699. DOI: https://doi.org/10.1108/INTR-05-2021-0294
View in Google Scholar - Yuan, L., Jiang, H., Shen, H., Shi, L., & Cheng, N. (2023). Sustainable development of information dissemination: A review of current fake news detection research and practice. Systems, 11(9), 458. DOI: https://doi.org/10.3390/systems11090458
View in Google Scholar - Zaidan, E., & Ibrahim, I. A. (2024). AI governance in a complex and rapidly changing regulatory landscape: A global perspective. Humanities and Social Sciences Communication, 11, 1121. DOI: https://doi.org/10.1057/s41599-024-03560-x
View in Google Scholar - Zannettou, S., Sirivianos, M., Blackburn, J., & Kourtellis, N. (2019). The web of false information: Rumors, fake news, hoaxes, clickbait, and various other shenanigans. Journal of Data and Information Quality, 11(3), 1–37. DOI: https://doi.org/10.1145/3309699
View in Google Scholar - Zhou, Q., Li, B., Scheibenzuber, C., & Li, H. (2023). Fake news land? Exploring the impact of social media affordances on user behavioral responses: Mixed-methods research. Computers in Human Behavior, 148, 107889. DOI: https://doi.org/10.1016/j.chb.2023.107889
View in Google Scholar - Zhou, J., Müller, H., Holzinger, A., & Chen, F. (2024). Ethical ChatGPT: Concerns, challenges, and commandments. Electronics, 13(17), 3417. DOI: https://doi.org/10.3390/electronics13173417
View in Google Scholar
Downloads
Download data is not yet available.