Prompting-Frameworks und die wahrgenommene Qualität KI-generierter Social-Media-Beiträge.
摘要
This article examines how structured prompting frameworks affect the perceived quality of AI-generated social media posts. Using an exploratory study, the RAF, RISE, and CARE frameworks are compared in a product campaign and a microlearning scenario. The basis for this is a theory-based evaluation framework with cognitive, affective, and behavioral dimensions, as well as additional quality and outcome criteria. Six AI-generated posts were evaluated by 17 participants. The results indicate context-dependent differences between the frameworks. RAF tends to be more frequently associated with cognitive quality, credibility, and usefulness, while RISE performs better in the campaign context in terms of affect- and intention-related criteria. The evaluation framework can be used as a tool for structured reflection on AI-supported text production in organizations.