Network segregation in a model of misinformation and fact checking
October 13, 2016 Β· Declared Dead Β· π Journal of Computational Social Science
"No code URL or promise found in abstract"
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Authors
Marcella Tambuscio, Diego F. M. Oliveira, Giovanni Luca Ciampaglia, Giancarlo Ruffo
arXiv ID
1610.04170
Category
cs.SI: Social & Info Networks
Cross-listed
cs.CY,
physics.soc-ph
Citations
45
Venue
Journal of Computational Social Science
Last Checked
6 months ago
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 is fact checking which, in some cases, is known to stop rumors from spreading further. However, fact checking may also backfire and reinforce the belief in a hoax. Here we take into account the combination of network segregation, finite memory and attention, and fact-checking efforts. 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 overall inform on the risks of uncontrolled misinformation online.
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