Understanding Deepfake Research and Trends through Topic Modelling.

Authors :: Chen, Chen
Goh, Dion Hoe‐Lian
Source :: Proceedings of the Association for Information Science & Technology. Oct2023, Vol. 60 Issue 1, p911-913. 3p.
Publication Year :: 2023
Abstract: Deepfake research has gained traction in recent years. Surveys have been conducted to summarize work on the detection and generation of deepfakes. However, a more comprehensive and quantitative overview that encompasses both technical and non‐technical areas is lacking. We address this gap using topic modelling to discover deepfake research topics in academic publications. Our results show that while detection techniques topics dominate the research field, other areas, such as privacy and legal research, offer potential avenues for further exploration. [ABSTRACT FROM AUTHOR]

Subjects :: *DEEPFAKES
*TECHNOLOGICAL innovations
*INFORMATION sharing
*INFORMATION policy
*ARTIFICIAL intelligence
*INFORMATION technology

Language :: English
ISSN :: 23739231
Volume :: 60
Issue :: 1
Database :: Academic Search Index
Journal :: Proceedings of the Association for Information Science & Technology
Publication Type :: Conference
Accession number :: 173115055
Full Text :: https://doi.org/10.1002/pra2.895