Replication Data for: 'Deepfakes: evolution and trends'

DOI

This study conducts research on deepfakes technology evolution and trends based on a bibliometric analysis of the articles published on this topic along with six research questions: What are the main research areas of the articles in deepfakes? What are the main current topics in deepfakes research and how are they related? Which are the trends in deepfakes research? How do topics in deepfakes research change over time? Who is researching deepfakes? Who is funding deepfakes research? We have found a total of 331 research articles about deepfakes in an analysis carried out on the Web of Science and Scopus databases. This data serves to provide a complete overview of deepfakes. Main insights include: different areas in which deepfakes research is being performed; which areas are the emerging ones, those that are considered basic, and those that currently have the most potential for development; most studied topics on deepfakes research, including the different artificial intelligence methods applied; emerging and niche topics; relationships among the most prominent researchers; the countries where deepfakes research is performed; main funding institutions. This paper identifies the current trends and opportunities in deepfakes research for practitioners and researchers who want to get into this topic.

Grant Information MCIN/AEI/10.13039/501100011033: PID2020-117912RB-C22 UPV/EHU: GIU21/037

Identifier
DOI https://doi.org/10.34810/data750
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/data750
Provenance
Creator García, Roberto ORCID logo; Gil, Rosa ORCID logo; Virgili-Gomà, Jordi ORCID logo; López-Gil, Juan-Miguel ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor García, Roberto; Universitat de Lleida
Publication Year 2023
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact García, Roberto (Universitat de Lleida)
Representation
Resource Type Process-produced; Dataset
Format text/csv
Size 3834101
Version 1.0
Discipline Other