Stochastic modeling analysis establishes explicit quasi-stationary distributions in rumor propagation frameworks, highlighting long-term pre-absorption dynamics across epidemic and information...
This paper examines the quasi-stationary behavior of stochastic rumor processes. Using the results by Doorn and Pollett (2008), we first prove that the continuous-time Maki–Thompson model has a unique quasi-stationary distribution (QSD) given by the point mass at the state ( 0 , 1 ) . To obtain a non-trivial QSD, we modify the absorption set by conditioning the process on not returning to the level 𝑦 = 1 after leaving the initial state ( 𝑁 , 1 ) . For this modified model, we establish the existence and uniqueness of a non-trivial QSD that assigns positive probability to all transient states, and then derive an explicit formula for this QSD in terms of paths and transition rates. We also discuss the ratio of expectations distribution as an alternative approach to describe the long-term behavior before absorption. The analysis is further extended to the Daley–Kendall rumor model and the stochastic SIR epidemic model.
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Ben-Ari et al. (2026) studied this question.
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