Digital Attention as a Market Salience Indicator: Predicting Fintech Market Performance with Computational Models

This study examines whether digital attention can serve as an engagement-based digital attention signal for fintech market performance. Using a revised panel of 70 firm-year observations from seven publicly verifiable fintech and payments firms over 2016–2025, the analysis combines financial outcomes, sector investment indicators, and digital variables related to web traffic, SEO visibility, social media presence, and app popularity. A Digital Attention Index (DAI) was constructed through arithmetic averaging and principal component analysis, with the first component explaining 82.39% of the digital-indicator variance. Fixed Effects models show that the DAI is positively and significantly associated with revenue, market capitalization, and net income, while sector investment is generally weak or insignificant. Out-of-sample validation confirms that panel Fixed Effects specifications outperform pooled OLS, Ridge, and Random Forest models. App popularity is the strongest standalone predictor for revenue and net income, while social media performs best for market capitalization. However, first-difference models weaken most relationships, and Granger tests indicate bidirectional temporal ordering, with financial performance often preceding digital attention. Overall, the findings support the DAI as a useful computational signal of fintech performance, while emphasizing that predictive and causal claims require cautious interpretation.