Mapping Artificial Intelligence-Driven Broadcasting Research: A Bibliometric Analysis of Content Production, Audience Engagement, and Personalized Media in the Digital Media Era

Abstract

The rapid development of digital technologies has significantly transformed the broadcasting industry, shifting traditional media systems toward highly interactive and data-driven digital environments. Among these technologies, artificial intelligence (AI) has emerged as a key driver of innovation in media production, audience analytics, and personalized content delivery. Despite the increasing adoption of AI technologies in broadcasting systems, the overall development and intellectual structure of research in this field remain fragmented across multiple disciplines. Therefore, this study aims to map the global research landscape of artificial intelligence–driven broadcasting using a bibliometric approach. This research employs bibliometric analysis to examine scientific publications related to artificial intelligence in broadcasting retrieved from the Dimensions.ai database. The dataset consists of 106 publications published between 2023 and 2025. The analysis was conducted using VOSviewer to identify publication trends, leading publication sources, geographic research distribution, highly cited publications, and keyword co-occurrence networks. The results indicate a consistent increase in publication output, suggesting that AI-driven broadcasting has become a rapidly expanding interdisciplinary research domain. The analysis also reveals that research in this field is distributed across engineering, communication, and journalism disciplines, reflecting the dual technological and socio-communicative nature of AI applications in media environments. Keyword network analysis further identifies several dominant research themes, including algorithmic systems, content recommendation technologies, newsroom transformation, and audience engagement. Overall, the findings demonstrate that artificial intelligence plays an increasingly important role in transforming broadcasting ecosystems by enabling automation in media production, improving personalized media experiences, and supporting data-driven audience engagement strategies in digital broadcasting platforms.

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