Summary statistics of cascade variables.

Emotional contagion on social media, particularly following shocking and tragic events, often unfolds through widespread resharing, amplifying affective responses that are typically intense and negative. This study focuses on the context of celebrity suicides, which have the potential to trigger emotional contagion and lead to adverse behavioral outcomes, such as copycat suicides. Using an exhaustive Twitter dataset covering four celebrity suicides, we theorize the propagation of emotional content through a valence-arousal framework, distinguishing emotions based on affective valence (positive or negative) and physiological arousal (high or low). We analyze how distinct emotions embedded in tweets propagate through retweet cascades, treating each tweet and its retweets as a single cascade. Propagation is measured across four cascade dimensions: size, lifetime, speed, and burstiness. Emotions are extracted from over a million tweets and retweets using a BERT-based language model and are used as predictors in regression analyses of the propagation metrics. Our results show that emotional messages propagate in distinct ways after tragic events. Disgust emerges as the most contagious emotion, spreading quickly, widely, and with longevity, while fear, despite its arousal, spreads weakly. Anger and surprise generate fast but short-lived cascades marked by high burstiness. Joy, though less frequent, endures longer than neutral and negative content, reflecting resilience but with lower burstiness. These findings advance research on online emotional propagation by demonstrating that discrete emotions differ significantly even within the same valence–arousal characteristic. They also offer insights for public health strategies to mitigate risks linked to emotional amplification in digital environments.