Algorithmic Truthfulness, Community Notes, and Trust in Greenwashing Claims: Evidence from Aspirational Fashion and Sustainable Luxury Brands

Abstract

The emergence of aspirational fashion and sustainable luxury brands occurs against the backdrop of growing environmental misinformation and greenwashing in today’s communicative ecology. At the same time, various social media platforms (e.g., X) have introduced hybrid verification systems that include Community Notes and combine automated assessments with crowd-sourced judgments. In light of this phenomenon, this paper presents an empirical investigation based on a mixed-method design, which involves (a) a theoretical review, (b) reinterpretation of two existing studies focusing on the use of AI and persuasive communication, and (c) a 2 × 2 factorial experiment (initial n = 240; valid n = 228) that tests the moderating role of Community Notes in the relationship between AI-generated messages and their credibility.

According to the findings, algorithmic personalization increases persuasiveness when AI-generated messages are supported by credible information; otherwise, they heighten concerns about greenwashing. Community Notes are interpreted as epistemic signals: they increase trust when a message is authentic and trigger more critical judgment when it contradicts expectations. Based on the observations, this research contributes to the scholarly literature by introducing an AI + Community framework that conceptualizes how AI, human judgment, and crowd wisdom interact to form sustainable credibility. Possible implications of the study center on the criteria for efficient communication governance in the age of automation.