Corrective Trust and Deinfluencing in Cryptocurrency Social Media Marketing

Abstract

The proliferation of financial content on social media has reshaped retail investors' decision-making, particularly in cryptocurrency markets marked by high uncertainty and weak institutional safeguards. While prior research has examined how digital influencers build trust and stimulate speculative behavior, little is known about how misplaced trust is actively corrected. This study conceptualizes deinfluencing as a counter-persuasion mechanism that recalibrates trust rather than redirecting it to alternative sources. Integrating trust theory, persuasion knowledge, and dual-process cognition, we propose the Corrective Trust Model, showing how deinfluencer content disrupts heuristic trust formation and activates analytical processing. Using a sequential mixed-methods design, findings indicate that deinfluencer exposure significantly reduces perceived trust and cryptocurrency investment intentions, advancing digital marketing and behavioral finance by theorizing trust correction as a protective cognitive mechanism.