Purpose: The research aims to visualize and analyze co-word network, and thematic clusters of the intellectual structure in the field of digital content management during 2010-2020. Method: The study is applied research with a descriptive approach which is conducted by techniques of co-word, and social network analysis. Data analysis and visualization of the co-word network were represented by SPSS, UCINet, and Python programming language. Findings: 8 main clusters are identified. The cluster multimedia content management & retrieval is the most mature and central thematic cluster. The USA and various sub-categories of Computer Science are located in the top ranks of WOS in the field. Most productions were published in 2020. Generally, the Clusters were labeled in two contexts of health and LAM (Libraries, Archives, Museums, and cultural heritage). Conclusion: Content-based management and retrieval are focused on artificial intelligence, decision-supported, knowledge-based and ontological techniques which are conducted as novel approaches and underlying trends in the field.
