Research Trends in AI-Driven Video Production A Systematic Bibliometric Investigation
Mus'ab Khalili Rosli Muhammad Farhan Fauzan Bin MasaatNur Muizz bin Mohamed SallehMohd Khairul Mustakim bin Mustapa KamalAhmad Khalid Bin Kamarul Saman
Aug 2026· e-Jurnal Penyelidikan dan Inovasi· 0 citations· 23 references
TL;DR
The intellectual evolution of this field from 2016 to 2026 is mapped, focusing on key publication trends and thematic shifts, indicating that the foundational frameworks of the field were established during that time.
Abstract
Artificial intelligence (AI) has fundamentally reshaped the world of video production, moving from simple automated edits to complex generative models capable of creating realistic content from scratch (Xie et al., 2025). This study maps the intellectual evolution of this field from 2016 to 2026, focusing on key publication trends and thematic shifts. A systematic bibliometric study of 2,371 peer-reviewed papers included in the Scopus database was carried out. The metrics included the total number of publications (TP), total citations (TC), the number of cited publications (NCP), average citations per publication (C/P), and average citations per cited publication (C/CP). The data reveals a massive surge in research output starting in 2021, with total publications reaching a peak of 796 in 2025. While volume is currently at an all-time high, the highest citation impact per paper occurred in 2019, indicating that the foundational frameworks of the field were established during that time. Thematically, research is clustered into four main areas: core technical architectures, media synthesis, deepfake detection and human ethics. This investigation provides a comprehensive roadmap for researchers navigating the fast growth of AI-driven media production.
A knowledge base that fuses established technology-adoption theories and structural-equation methodology with recent generative-AI manifestos is revealed, organised around four themes: content production, distribution channels, audience reach and responsible governance.
Kai Quan, A. Kasim, R. Mijan· International Review of Mana...· 0 citations
A comprehensive bibliometric analysis of global generative AI research to characterize its publication growth, disciplinary and geographical distribution, institutional participation, funding patterns, citation performance, and thematic development provides an evidence-based, multidimensional characterization of the ra...
Sofia Stamou, Matina Kiourexidou· Information· 0 citations
The results reveal a strong increasing trend in post-2019 publications due to the accelerated progress of natural language processing, machine learning, and generative systems such as ChatGPT, and sheds light on the cognitive framework and world process of AI-driven research communication and implications for future ac...
P. Tyagi, S. Sharma· International Journal of Inf...· 0 citations
The rapid advancement of generative artificial intelligence (AI) has fundamentally transformed the creation, perception, and societal implications of visual and literary art. The present study presents the first comprehensive bibliometric analysis of SSCI- and A&HCI-indexed scholarship on AI-generated art, drawing on 2...
En-Ci Huang, Qi-Jun Song· Liberal Arts and Social Scie...· 0 citations
A bibliometric analysis on Artificial Intelligence for Inclusive Education as an emerging research trend particularly in between the years of 2021–2025 suggests integration of AI technologies in education systems through providing valuable insights for educators, researchers and policymakers.
This research provides a detailed bibliometric analysis of AI in education publications using Scopus indexed data from 2015 to 2025, illustrating the fast-paced growth of the field and the structural tensions that arise in this process, paving the way for future studies that seek to deepen the qualitative, ethical, and...
Smail Kannaoui, Fathalah Elwahab, Nour El Houda Derkaoui et al.· Discover Education· 0 citations
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