Who Gets the Flows? AI-Based Brand Visibility, Social Media Sentiment, and Capital Allocation in the U.S. Spot Bitcoin ETF Market

This study examines whether retail social media sentiment and community attention explain daily net capital flows into U.S. spot Bitcoin exchange-traded funds (ETFs), and whether issuer brand visibility conditions that relationship. We construct a balanced panel of N=10 ETFs over T=514 trading days (January 2024 to January 2026) and combine it with 162,819 cleaned Reddit posts to derive three AI-driven discourse variables: engagement-weighted sentiment, community attention, and a novel issuer-specific BrandScore. Entity fixed-effects regressions show that neither aggregate sentiment nor BrandScore level alone significantly predicts fund-level flows; however, the Sentiment × BrandScore interaction is significant (β^=2.930, p=0.038), indicating that sentiment becomes economically meaningful only when attached to a visible issuer. This interaction survives two-way (entity + date) fixed effects (p=0.012) and winsorization (p=0.004). Panel quantile regressions reveal distributional heterogeneity in the brand-sentiment channel. Rolling 90-day window estimation confirms the mechanism is episodic, with the interaction achieving significance in 62.8% of subsample windows. These results provide suggestive evidence for a brand-filtered sentiment transmission mechanism in digital asset markets.