NextFin news, Researchers led by Stefano Zapperi from the University of Milan published a study on Wednesday in the journal Nature revealing that the spread of rumors during the Great Fear of 1789 in rural France followed predictable trajectories similar to infectious disease transmission. The Great Fear, a wave of panic and unrest that occurred between late July and early August 1789, was a pivotal moment at the onset of the French Revolution, marked by widespread rumors of aristocratic plots and armed brigands.
Using epidemiological models typically applied to disease spread, the research team reconstructed the transmission network of rumors from town to town by digitizing 18th-century French road maps and integrating extensive historical data including local chronicles, parish records, and administrative documents. This allowed them to create a dynamic spatiotemporal dataset mapping how panic propagated across the French countryside.
The study found that rumors spread at an average speed of 45 kilometers per day along the road network, with 40% of affected locations situated near postal relay stations. Contrary to previous interpretations that viewed the Great Fear as a chaotic emotional outbreak, the analysis demonstrated that the spread was highly structured and influenced by socio-economic variables such as population density, literacy rates, wheat prices, and land ownership laws.
Notably, the research showed that more populous and literate urban centers acted as hubs that amplified and retransmitted information with greater authority and speed. These findings challenge the traditional historiographical view that the panic was purely irrational, instead highlighting the role of systemic social and economic factors in shaping the diffusion of misinformation.
The Great Fear led to the formation of peasant militias and attacks on feudal estates, culminating in the National Assembly's abolition of feudal privileges on August 4, 1789. The study's authors suggest that understanding the mechanisms behind this historical spread of misinformation offers valuable insights into contemporary challenges posed by disinformation in digital networks.
The research was published on Wednesday, August 27, 2025, and is available through Nature. It was conducted without external funding and draws on interdisciplinary expertise in history, epidemiology, and data science.
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