Rumor spreading refers to how unverified or unsubstantiated claims propagate through social networks. In the misinformation literature, rumor models and empirical studies of rumor cascades provide insight into the structural and social factors that enable false claims to reach millions of users before fact-checks can circulate.
Rumors differ from deliberate disinformation in origin (spontaneous vs. coordinated production) but share similar propagation mechanisms: social proof, selective exposure, network homogeneity, and confirmation bias all drive rapid diffusion. A key finding across studies is that cascade size depends less on the truth value of the rumor and more on network structure, user polarization, and algorithmic amplification.
Key papers
- Del Vicario et al. (2016) — The spreading of misinformation online — Data-driven analysis of how rumors spread through homogeneous social networks on Facebook; introduces percolation model showing that homogeneity and polarization, not content quality, are the primary determinants of cascade size; models rumor spreading as branching process with sharing threshold and network connectivity parameters.
Related topics
- misinformation (false information and belief)
- Information Cascades (mathematical models of spreading)
- echo-chambers (network structure enabling rumor growth)
- polarization (user-level property shaping rumor receptivity)