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Generation Mechanisms and Communication Strategies of Yunnan Ethnic Cultural Digital IP from the Perspective of Multimodal AIGC

Author(s)

Qianyu Liu

Affiliation(s)

School of Arts and Media, Yunnan College of Business Management, Kunming, Yunnan, China

Abstract

The rapid advancement of artificial intelligence-generated content (AIGC) is transforming the production, representation, and dissemination of cultural heritage. Multimodal AIGC integrates text, images, audio, video, and spatial content, creating opportunities for the digital transformation of ethnic cultural resources. Yunnan Province possesses diverse cultural traditions that provide substantial potential for developing distinctive cultural digital intellectual property (IP). However, fragmented cultural representation, insufficient semantic interpretation, inconsistent multimodal outputs, and weak cross-platform coordination remain important challenges. Drawing on cultural semiotics, digital storytelling, and participatory culture, this conceptual study proposes a five-stage generation mechanism encompassing cultural resource acquisition, semantic knowledge modeling, multimodal collaborative generation, digital narrative construction, and human–AI evaluation. It further develops a communication strategy integrating differentiated content, cross-platform dissemination, participatory co-creation, immersive experiences, and sustainable IP governance. The proposed framework emphasizes cultural authenticity, community participation, provenance, and ethical oversight. It offers a research agenda for prototype development and empirical evaluation rather than claiming verified implementation outcomes.

Keywords

Multimodal AIGC; Yunnan Ethnic Culture; Digital Intellectual Property; Cultural Heritage; Digital Storytelling; Communication Strategies

References

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