Stiffness Analysis to Predict the Spread Out of Fake Information

Raffaele D’Ambrosio, Giuseppe Giordano, Serena Mottola and Beatrice Paternoster
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Raffaele D’Ambrosio: Department of Information Engineering and Computer Science and Mathematics, University of L’Aquila, 67100 L’Aquila, Italy
Giuseppe Giordano: Department of Mathematics, University of Salerno, 84084 Fisciano, Italy
Serena Mottola: Department of Economic and Legal Studies, University “Parthenope” of Naples, 80133 Naples, Italy
Beatrice Paternoster: Department of Mathematics, University of Salerno, 84084 Fisciano, Italy

Future Internet, 2021, vol. 13, issue 9, 1-10

Abstract: This work highlights how the stiffness index, which is often used as a measure of stiffness for differential problems, can be employed to model the spread of fake news. In particular, we show that the higher the stiffness index is, the more rapid the transit of fake news in a given population. The illustration of our idea is presented through the stiffness analysis of the classical SIR model, commonly used to model the spread of epidemics in a given population. Numerical experiments, performed on real data, support the effectiveness of the approach.

Keywords: fake news; SIR model; stiffness ratio (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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