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Publication, Collaboration, Citation Performance, and Triple Helix Innovation Gene of Artificial Intelligence Research in the Communication Field: Comparing Asia to the Rest of the World

Author

Listed:
  • Yu Peng Zhu

    (Chongqing University)

  • Han Woo Park

    (Yeungnam University)

Abstract

Artificial intelligence (AI) in the communication field has become increasingly popular in recent years. This study collected data from 482 documents and cited references in the Web of Science database. It explores the knowledge structure related to AI in communication, combined with the triple helix innovation gene model. The analysis employed collaborative network analysis, two-mode network analysis, citation analysis, and quadratic assignment procedure-based correlation analysis. The results show that the most popular hotspots are human–machine communication, automatically generated publications, social media-mediated fake news, and some other AI-based applied research. Academic collaborations can be facilitated by transnational disciplinary leaders. China emerged as the core academic country with the greatest growth potential in Asia, while the core non-Asian country is the United States. In addition, the trend in collaboration among scholars in Asia is better than in non-Asian countries. However, concerning the characteristics of collaborating institutions, the triple-helix collaboration among universities, government bodies, and industries remains insufficient. Particularly, the collaboration between industry and government necessitates further development.

Suggested Citation

  • Yu Peng Zhu & Han Woo Park, 2025. "Publication, Collaboration, Citation Performance, and Triple Helix Innovation Gene of Artificial Intelligence Research in the Communication Field: Comparing Asia to the Rest of the World," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 10308-10328, June.
    • Handle: RePEc:spr:jknowl:v:16:y:2025:i:2:d:10.1007_s13132-024-02280-6
    DOI: 10.1007/s13132-024-02280-6
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