Talking to Digital Twins: Selective Disclosure and Belief Measurement in Financial Social Media

Abstract:Social media affect financial markets, but public posts by financial media personas are voluntary disclosures. What is not disclosed is therefore usually unobserved. We address this measurement problem by conducting repeated, real-time interviews of "digital twins" built from monitored finfluencers' X accounts under a fixed protocol. The interviews recover stock-level public-persona belief proxies even when no public recommendation is made. Because the interviews are generated and archived before the relevant return windows, the design avoids the look-ahead bias that arises when LLMs are queried ex post. The evidence shows that information obtained from these digital-twin interviews predicts the cross section of large-cap stock returns in the expected direction. Repeated real-time interviews therefore show how selective disclosure can be turned into measurable panels of market views.

General Economics (econ.GN); Artificial Intelligence (cs.AI)

arXiv:2608.01181 [econ.GN]

(or arXiv:2608.01181v1 [econ.GN] for this version)

https://doi.org/10.48550/arXiv.2608.01181 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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