On a Model of Rumors Spreading Through Social Media

Rumors have become a serious issue in today's modern era, particularly in view of increased activity in social and online platforms. False information can go viral almost instantaneously through social networks, which immediately affect society and people's minds. The form of rumor it develops within, whether fabricated intentionally or not, impacts public perspectives through manipulation of emotion and cognition. We propose and analyze a mathematical model describing how rumors can spread through an online social media (OSM) platform. Our model focuses on two coexisting rumors (two strains). The results provide some conditions under which rumors die out or become persistent, and they show the influence of delays, skepticism levels, and incidence rates on the dynamics of information spread. We combine analytical tools (Routh-Hurwitz tests and delay-induced stability switches) with MATLAB/Python simulations to validate the theoretical predictions.

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Publication Details

Journal
Entropy
Published
2025-08-26
DOI
https://doi.org/10.3390/e27090903
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
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article

On a Model of Rumors Spreading Through Social Media

A. Halanay, Florin Avram, Laurance Fakih
Entropy
Misinformation and Its Impacts
article

On a Model of Rumors Spreading Through Social Media

A. Halanay, Florin Avram, Laurance Fakih
article en

Abstract

Rumors have become a serious issue in today's modern era, particularly in view of increased activity in social and online platforms. False information can go viral almost instantaneously through social networks, which immediately affect society and people's minds. The form of rumor it develops within, whether fabricated intentionally or not, impacts public perspectives through manipulation of emotion and cognition. We propose and analyze a mathematical model describing how rumors can spread through an online social media (OSM) platform. Our model focuses on two coexisting rumors (two strains). The results provide some conditions under which rumors die out or become persistent, and they show the influence of delays, skepticism levels, and incidence rates on the dynamics of information spread. We combine analytical tools (Routh-Hurwitz tests and delay-induced stability switches) with MATLAB/Python simulations to validate the theoretical predictions.

EntropyVol. 27(9)
Laboratoire de Mathématiques Blaise Pascal (FR), Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Openalex Percentile: Top 70%
Misinformation and Its Impacts
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