Mario Haim

Capturing the dynamics of online news

A changing media environment and decreasing revenue requires online journalism to adapt to the dynamics of an online »marketplace of attention« 2014) by publishing fast and often, appealing to users, and through a multitude of distribution channels. Yet, this adaptation entails challenges to journalism research since such dynamics in online news are difficult to capture. Thus, this methodological study sets out to provide a more thorough understanding of news outlets’ publishing and updating patterns to derive adequate recommendations for data capturing within the dynamics of online news. Data originates from an automated online observation of five exemplary news outlets over the course of six months, resulting in 53,356 captured articles and 260,963 captured homepages. The results highlight the underlying assumption that online news follow different dynamics than legacy news, illustrating online news’ constant and short-lived but at the same time almost static character since updates on single articles are rare. For future studies, the findings suggest capturing online news continuously and on rather short notice, homepages and individual articles deserve separate and differentiated consideration.

Keywords: online news, data capture, sampling, web scraping, observation, content analysis

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