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According to previous research, online news production is characterized by the volatility and fast pace of reporting as well as by the interplay of various contributors to news flows within the online news ecosystem. However, as both concepts are challenging to study, research discovering the dynamics of news flows at the ecosystem level is rare. Utilizing techniques of automated content analysis and big databases of online news content, this paper proposes an approach to make the pace and dynamics of news diffusion processes among online news sites observable. It reviews several lines of argument for the fast pace of online news production based on “breaking news” coverage, immediacy as a norm, and imitation among online news providers. Applying an analytical framework from diffusion of news events research, we find recurring dynamics for the diffusion processes of 95 events among 28 German online news sites. We distinguish three clusters of diffusion processes based on their temporal patterns. On average, it takes only 1.5 hours for a majority of online news sites to report news of the 43 events in the largest cluster. The narrow timing of broadly shared news decisions within the ecosystem reveals a strong potential for abrupt surges or bursts in online news flows.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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