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This study offers the first large-scale analysis of the semantic contexts of “news” in podcasting. Drawing on field theory and a purposively constructed sample of more than 50,000 English-language podcasts that invoke “news” in their metadata, we use semantic network analysis to identify distinct communities, and topic modeling to examine thematic variation within the network core. Results reveal substantial heterogeneity surrounding the shared label, with journalistic, political, commercial, cultural, and specialized forms of public-affairs language occupying overlapping portions of the same semantic space. We interpret this differentiation as consistent with heteronomous conditions within an institutionalizing podcast field, where “news” is positioned as an information brokerage term across specialized topic domains. We conclude by discussing isomorphism and its implications for the autonomy and boundaries of professional journalism.
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Diehl et al. (2026) studied this question.
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