Abstract
This paper establishes a methodology to elicit and quantify narratives from survey data using textual analysis. We extract thirteen narratives from daily US stockholder questionnaires conducted during the first-wave COVID-19 period and measure their prevalence over time. Survey-based narratives positively correlate with their news and social media analogs, but equivalence is rejected. This discrepancy between sources, arising from social transmission, increases markedly when uncertainty prevails and enforces a negative bias in narrative tone. Information percolation between sources is unidirectional, but heterogeneous across narratives. Narrative importance is evident from their relation to political identity, physical mobility, risk premia, and economic fluctuations.
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