Communications in Humanities Research ISSN: 2753-7072
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Research Article

Statistical Measurement of F1 Fan Attention Dynamics: Competitive Performance, Media Exposure, and Social Interaction

Lingrui Zhou*
High School Affiliated to Nanjing Normal University Jiangning Campus

* Corresponding author: [email protected]

Abstract

With the expansion of F1 racing across social media, search platforms, and streaming media, driver attention has gradually become a continuously observable data point. Existing research typically uses Google Trends, fan size, fan growth, and engagement rate to measure changes in attention, but these indicators correspond to search attention, cumulative audience, and immediate engagement, respectively, and their statistical meanings are not interchangeable. Regarding driving factors such as competitive performance, race suspense, media exposure, and social interaction, relevant literature employs methods such as linear regression, count regression, panel models, event studies, and nonparametric tests. Existing evidence shows that F1 fan attention exhibits time dependence, long-tail distribution, cardinality effects, and platform heterogeneity, and there is also endogeneity between media exposure and competitive performance. Statistical analysis requires first distinguishing between Search, Growth, and Engagement, then selecting a model based on the distribution of the dependent variable and the data structure, and controlling for individual differences and time impacts through fixed effects, event windows, and robust standard errors. This establishes an analytical path from indicator measurement and driving factors to dynamic identification, providing a statistical foundation for the quantitative comparison of F1 fan attention and subsequent driver-level panel analysis.

Keywords: Fan Attention; Mathematical Statistics; Social Media; Panel Data; Event Study
Published: October 13, 2026
DOI: 10.54254/2753-7064/2026.BA37579
Volume: CHR Vol.123
pp. 61-67
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