Kwon, HyerinLu, LinqiKang, JiwonMcleod, Douglas2024-12-262024-12-262025-01-07978-0-9981331-8-8122fc15d-502f-4458-9390-bbd2a301d35chttps://hdl.handle.net/10125/109119This study explores the application of ChatGPT (GPT) to content analysis within the context of framing research, specifically examining its effectiveness in identifying public health, economic stability, and civic vitality frames in COVID-19 press releases. Our methodology is grounded in the Semantic Architecture Model (SAM), which conceptualizes framing as a process by which meaning is embedded in content units at various textual levels (i.e., concepts, assertions, arguments and narratives). In addition, this study underlines the necessity of AI prompt engineering to improve GPT’s coding performance in identifying frames at the concept, assertion, and thematic argument levels. The findings indicate the transformative potential of AI in communication research, highlighting its ability to analyze complex message framing across diverse contexts.10Attribution-NonCommercial-NoDerivatives 4.0 InternationalCommunication, Digital Conversation, and Media Technologieschatgpt, content analysis, framing, prompt engineering, semantic architecture modelConference Paper10.24251/HICSS.2025.279