Virality: What Makes Narratives Go Viral, and Does it Matter?

The effectiveness of political narratives as a communication technology depends on their virality and on the persuasiveness of single narrative exposure. To analyze narratives empirically, we introduce the political narrative framework and a pipeline for its measurement using large language models (LLMs). It captures the essence of a narrative by its characters, who are cast as neutral or in one of three drama triangle roles: the hero, villain, or victim. Using 1.15 million U.S. climate policy tweets from 2010–2021, we find that political narratives are consistently more viral than comparable neutral tweets. This result is robust to conditioning on a rich set of fixed effects, author characteristics, language metrics and emotionality. Hero roles increase virality by 56\%, but the biggest virality boost stems from using villain roles (152\%) and from combining other roles with villain characters. To examine the persuasiveness of single exposure to some of the most frequent and viral character-role combinations, we use three pre-registered online experiments with 3000 participants. The results show that narrative exposure influences beliefs and revealed preferences about a character, while a single exposure is not sufficient to move support for specific policies. Political narratives also lead to consistently higher memory of the narrative characters and their roles, while memory of objective facts is not improved. Taken together, the political narrative framework provides a measure that moves beyond emotions and linguistic features, helps to explain virality, and is linked to shifts in beliefs, revealed preferences, and memory.