Comparing information diffusion mechanisms by matching on cascade size

Jonas L. Juul and Johan Ugander
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Jonas L. Juul: a Center for Applied Mathematics, Cornell University, Ithaca, NY 14853;
Johan Ugander: b Management Science and Engineering, Stanford University, Stanford, CA 94305

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 46, e2100786118

Abstract: Do different types of information spread differently online? In recent years, studies have sought answers to such questions by comparing statistical properties of network paths taken by different kinds of content diffusing online. Here, we demonstrate the importance of controlling for correlations between properties being compared. In particular, we show that previously reported structural differences between diffusion paths of false and true news on Twitter disappear when comparing only cascades of the same size; differences between diffusion paths of images, videos, news, and petitions persist. Paired with a theoretical analysis of diffusion processes, our results suggest that, in order to limit the spread of false news, it may be enough to focus on reducing the mean “infectiousness” of the information.

Keywords: information diffusion; network analysis; social media; misinformation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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