A Visual Analysis of Visual Style Research in Digital Media Arts from the Knowledge Graph Perspective

This paper systematically reviews the current research status on the visual style of digital media art. It analyzes a selected set of 1604 articles retrieved from the Web of Science core collection database using visualization tools like VOSviewer and CiteSpace. Through knowledge map-based analysis across dimensions such as authors, journal publication volumes, sources, co-occurrence networks of keywords, keyword clustering, and bursts, this study uncovers hotspots, trends, and frontiers in this field, offering insights into future research avenues. Findings indicate four primary categories in studying the visual style of digital media art: science and technology, communication, aesthetics, and the art's historical aspects, marking a shift from generalization to specialization and disciplinary to interdisciplinary diversification. Emerging directions encompass human-computer interaction, artificial intelligence, algorithmic art, and NFT art. In summary, this paper contributes to comprehending the current landscape and acts as a compass in scientific literature, providing valuable perspectives for advancing ontology research in digital media art.