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Reciprocal spreading and debunking processes of online misinformation: A new rumor spreading–debunking model with a case study

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  • Jiang, Meiling
  • Gao, Qingwu
  • Zhuang, Jun

Abstract

In this digital era, massive digital misinformation was ranked first by the World Economic Forum among the top future global risks. As human and financial resources are limited, governments or companies would like to use the optimal level of debunking effort and the most efficient debunking strategy. There exists a rich literature that studies the rumor spreading process on social media. However, a huge gap exists on studying the simultaneous propagation of false rumors and debunking information, and the interplay between them. The spreading of rumors and anti-rumors is a dynamic and reciprocal process. Acknowledging that effective debunking strategy is a potential tool to reduce the loss of massive digital misinformation, this paper proposes a novel rumor spreading–debunking (RSD) model by ordinary differential equation (ODE) system to explore the interplay mechanism between rumor spreading and debunking processes. We derive and discuss the key factors and parameters that influence the debunking process. Firstly, we consider the spreading pattern of a rumor before Debunkers appear based on the Susceptible–Infected–Recovered (SIR) model with its own characteristics of rumor, and obtain a series of results including the final scope of the rumor spreading, the maximal scale of the rumor spreader, the number of Stiflers at any time point, and the popularity level of the rumor. Secondly, with the data from the real world rumor case, which is the ”Immigration Rumor” during Hurricane Harvey in 2017, we determine the case-specific parameters, and validate our model by comparing the simulated curve with the real data. Our model helps to understand the impact of the rumor on the social media, and predict the future trend. Finally, we use our model to simulate the influence of different debunking strategy, and identify more efficient debunking measures that should be used by the government officials or companies when facing rumor mill under different situations.

Suggested Citation

  • Jiang, Meiling & Gao, Qingwu & Zhuang, Jun, 2021. "Reciprocal spreading and debunking processes of online misinformation: A new rumor spreading–debunking model with a case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    • Handle: RePEc:eee:phsmap:v:565:y:2021:i:c:s0378437120308700
    DOI: 10.1016/j.physa.2020.125572
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    References listed on IDEAS

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    3. Jamalzadeh, Saeed & Mettenbrink, Lily & Barker, Kash & González, Andrés D. & Radhakrishnan, Sridhar & Johansson, Jonas & Bessarabova, Elena, 2024. "Weaponized disinformation spread and its impact on multi-commodity critical infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

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