Affiliation:
1. Institute of Engineering and Technology, Chitkara University, Punjab 140601, India
2. School of Creative Technologies, University of Bolton, A676 Deane Rd., Bolton BL3 5AB, UK
3. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore 632014, India
Abstract
The unregulated proliferation of counterfeit news creation and dissemination that has been seen in recent years poses a constant threat to democracy. Fake news articles have the power to persuade individuals, leaving them perplexed. This scientometric study examined 569 documents from the Scopus database between 2012 and mid-2022 to look for general research trends, publication and citation structures, authorship and collaboration patterns, bibliographic coupling, and productivity patterns in order to identify fake news using deep learning. For this study, Biblioshiny and VOSviewer were used. The findings of this study clearly demonstrate a trend toward an increase in publications since 2016, and this dissemination of fake news is still an issue from a global perspective. Thematic analysis of papers reveals that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, as well as fake news, are crucial but underdeveloped, while studies on deep fake detection, digital contents, digital forensics, and computer vision constitute niche areas. Furthermore, the results show that China and the USA have the strongest international collaboration, despite India writing more articles. This paper also examines the current state of the art in deep learning techniques for fake news detection, with the goal of providing a potential roadmap for researchers interested in undertaking research in this field.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference80 articles.
1. Rajan, B. (2019). Handbook of Research on Deception, Fake News, and Misinformation Online, IGI Global.
2. Fake news as a two-dimensional phenomenon: A framework and research agenda;Egelhofer;Ann. Int. Commun. Assoc.,2019
3. Lahby, M., and Yassine, M. (2022). Combating Fake News with Computational Intelligence Techniques, Springer.
4. Sharma, S., and Sharma, D.K. (2019, January 21–22). Fake News Detection: A Long Way to Go. Proceedings of the 2019 4th International Conference on Information Systems and Computer Networks (ISCON), Mathura, India.
5. Bran, R., Tiru, L., Grosseck, G., Holotescu, C., and Malita, L. (2021). Learning from each other—A bibliometric review of research on information disorders. Sustainability, 13.
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献