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  • Open Access

Virality detection and control strategies in rumor models

Eva Rifà*

Julian Vicens

Emanuele Cozzo

  • *Contact author: eva.rifa@eurecat.org
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Phys. Rev. Research 8, 013313 – Published 24 March, 2026

DOI: https://doi.org/10.1103/2bh8-p6rx

Abstract

We study the dynamics and intervention strategies of a rumor using the modified Maki-Thompson model. A key challenge in social networks is distinguishing between natural increases in transmissibility and artificial injections of rumor spreaders, such as through broadcast events or astroturfing. Using stochastic simulations, we compare two scenarios: one with organic growth in transmissibility and another with externally injected spreaders. Although both lead to high autocorrelation, only the organic growth produces oscillatory patterns in autocorrelation at multiple lags, an effect we can analytically explain using the N-intertwined mean-field approximation. This distinction offers a practical tool to identify the origin of rumor virality and also infer its transmissibility. Our approach is validated analytically and tested on real-world data from Twitter during the announcement of the Higgs boson discovery. In addition to detection, we also explore control strategies. We show that the average lifetime of a rumor can be manipulated through targeted interventions: placing spreaders at specific locations in the network. Depending on their placement, these interventions can either extend or shorten the lifespan of the rumor.

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Phys. Rev. Research 8, 013313– Published 24 March, 2026
  • Received 7 October 2025
  • Accepted 18 February 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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