SPREAD, a framework and open-source R toolbox to quantify behavioural contagion

Abstract Behavioural contagion, when one individual’s behaviour increases the likelihood of similar behaviours in others, is a fundamental dimension of social interaction, yet its empirical quantification remains methodologically challenging. Distinguishing contagion from coincidental co-occurrence, resolving contagion across continuous latencies rather than within fixed windows, accounting for behavioural base rates, and incorporating social structure require integrated analytical solutions. We present SPREAD, a conceptual and statistical framework implemented as an open-source R toolbox for quantifying behavioural contagion in time-series interaction data. SPREAD compares observed behavioural sequences with null distributions generated from permuted data that preserve individual event frequencies while disrupting inter-individual temporal alignment. The framework yields latency-resolved, base-rate corrected estimates of contagion strength that are comparable across behaviours and social configurations. We demonstrate SPREAD across two behavioural domains, laughter and eating, using human triadic data and illustrate its ability to detect contagion effects across distinct temporal dynamics.