The simple regularities in the dynamics of online news impact

Matúš Medo (), Manuel S. Mariani and Linyuan Lü
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Matúš Medo: University of Electronic Science and Technology of China
Manuel S. Mariani: University of Electronic Science and Technology of China
Linyuan Lü: University of Electronic Science and Technology of China

Journal of Computational Social Science, 2022, vol. 5, issue 1, No 27, 629-646

Abstract: Abstract Online news can quickly reach and affect millions of people, yet we do not know yet whether there exist potential dynamical regularities that govern their impact on the public. We use data from two major news outlets, BBC and New York Times, where the number of user comments can be used as a proxy of news impact. We find that the impact dynamics of online news articles does not exhibit popularity patterns found in many other social and information systems. In particular, we find that a simple exponential distribution yields a better fit to the empirical news impact distributions than a power-law distribution. This observation is explained by the lack or limited influence of the otherwise omnipresent rich-get-richer mechanism in the analyzed data. The temporal dynamics of the news impact exhibits a universal exponential decay which allows us to collapse individual news trajectories into an elementary single curve. We also show how daily variations of user activity directly influence the dynamics of the article impact. Our findings challenge the universal applicability of popularity dynamics patterns found in other social contexts.

Keywords: Online information; Dynamics of impact; Collective attention; Evolving networks (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s42001-021-00140-w

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