Human-AI Co-Creation on Social Media: Interview Data and Qualitative Coding Dataset

This dataset contains the qualitative research materials supporting the study “Human-AI Co-Creation on Social Media: AI Involvement, Content Authenticity, and Consumer Engagement.” The dataset documents the interview-based investigation of how consumers interpret the roles of humans and generative artificial intelligence (AI) in social media content creation, and how these interpretations relate to perceived content authenticity, trust, and consumer engagement. The dataset includes pseudonymized informant profiles, a semi-structured interview guide, interview transcripts, initial coding, focused coding, thematic categorization, an NVivo-style coding structure, and an analytical memo. Six informants participated in the study, identified using pseudonyms to protect confidentiality. The interviews were originally conducted in Indonesian, while the transcript materials included in this repository are provided in English translation for international dissemination. The qualitative analysis focuses on five main analytical domains: (1) AI involvement, (2) perceived human contribution, (3) content authenticity, (4) trust and emotional connection, and (5) consumer engagement. The resulting thematic structure examines AI as a creative assistant, human control in co-creation, authenticity as an expression of human identity, transparency and perceived effort, and context-dependent consumer engagement. This dataset is intended to support transparency, traceability, and reproducibility of the qualitative analysis reported in the related manuscript. The materials may also support future research on human-AI collaboration, generative AI in social media marketing, authenticity perceptions, AI disclosure, and consumer engagement. Informant identities are protected through the use of pseudonyms.