Witchcraft as Narrative Contagion: Modeling the Diffusion and Mutation of Transmission Mechanisms in the 1692 Salem Crisis
Sen, Protiva
Sen, Protiva
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Abstract
Social contagion research has flourished by asking how information spreads from one individual to others. Yet a parallel question has received far less formal attention: how does the narrative being spread mutate into additional narratives? How does one story become two stories? We call this narrative contagion, and we argue it operates as a second-order diffusion process layered atop conventional social transmission. Crucially, we treat mutation as a dynamical property, where narrative variants can gain or lose transmission strength as they propagate. The Salem witch trials of 1692 offer an extraordinary natural laboratory for this question. Over nine months, more than 150 individuals were accused of witchcraft, and in 19 cases executed. The trial record is rich and unusually structured: accusers were required to describe not merely that someone had afflicted them, but how, the precise mechanism by which harm was alleged to have occurred. These mechanisms range from spectral apparitions and physical touch to book signing, animal familiars, rituals, food-based inducements, and coercive threats. Each testimony thus encodes both a relational event (accuser ? accused) and a mechanism label. We construct a manually annotated relational event dataset from 983 trial documents, capturing directed interactions of the form Accuser ? Mechanism ? Accused. We represent these data as a temporal bipartite network and analyze how mechanism usage evolves across time and social structure. Our framework generates three expectations: mechanism usage will exhibit temporal autocorrelation; mechanism adoption will follow network proximity; and mechanism diversity will expand as new variants emerge and later contract as dominant narratives crowd out alternatives. Using network-based diffusion analysis and regression models, we test whether network exposure predicts mechanism adoption beyond independent invention. This project introduces a replicable pipeline for extracting structured relational events and offers a formal account of narrative contagion as a measurable diffusion process.
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Date
1/1/2026
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Graduate Student
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Poster
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Computer Science
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College of Engineering and Mathematical Sciences
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Social Science