Network segregation in a model of misinformation and fact-checking

Marcella Tambuscio (), Diego F. M. Oliveira, Giovanni Luca Ciampaglia () and Giancarlo Ruffo
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Marcella Tambuscio: University of Turin
Diego F. M. Oliveira: Indiana University
Giovanni Luca Ciampaglia: Indiana University
Giancarlo Ruffo: University of Turin

Journal of Computational Social Science, 2018, vol. 1, issue 2, No 2, 275 pages

Abstract: Abstract Misinformation under the form of rumor, hoaxes, and conspiracy theories spreads on social media at alarming rates. One hypothesis is that, since social media are shaped by homophily, belief in misinformation may be more likely to thrive on those social circles that are segregated from the rest of the network. One possible antidote to misinformation is fact checking which, however, does not always stop rumors from spreading further, owing to selective exposure and our limited attention. What are the conditions under which factual verification are effective at containing the spreading of misinformation? Here we take into account the combination of selective exposure due to network segregation, forgetting (i.e., finite memory), and fact-checking. We consider a compartmental model of two interacting epidemic processes over a network that is segregated between gullible and skeptic users. Extensive simulation and mean-field analysis show that a more segregated network facilitates the spread of a hoax only at low forgetting rates, but has no effect when agents forget at faster rates. This finding may inform the development of mitigation techniques and raise awareness on the risks of uncontrolled misinformation online.

Keywords: Misinformation; Fact-checking; Information diffusion; Network segregation; Agent-based modeling (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s42001-018-0018-9

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