Co-evolution of Rumor Diffusion and Structural Stability in Signed Social Networks

Prediction and control of rumor diffusion in social networks (SNs) are closely tied to the underlying connectivity patterns. Contrary to most existing efforts that exclusively focus on positive social user interactions, the impact of contagion processes on the temporal evolution of signed SNs with distinctive friendly (positive) and hostile (negative) relationships yet, remains largely unexplored. In this paper, we study the interplay between social link polarity and propagation of intentionally fabricated information coupled with user alertness. In particular, we propose a novel energy model built on Heider’s balance theory that relates the stochastic susceptible-alertinfected-susceptible rumor epidemic model with the structural balance of signed SNs to substantiate the trade-off between social tension and rumor spread. Moreover, the role of hostile social links in the formation of disjoint friendly clusters of alerted and infected users is analyzed. Using three real-world datasets, we further present a time-efficient algorithm to expedite the energy computation in our Monte-Carlo simulation method and show compelling insights on the effectiveness and rationality of user awareness and initial network settings in reaching structurally balanced local and global network energy states.