ArtifactShow: Incorporating Generative AI into Narrative Visualization for Interactive Cultural Experience

Ningning Xu, Yu Liu, Yifei Chen, Zheyuan Jiang, Yuwei Ren, Zhichao Zhang, Bin Jia, Lingyun Yu*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

We propose ArtifactShow, an interactive system that engages users in cultural experiences through a series of digital shows powered by generative AI. Current cultural digitization processes rely heavily on labor-intensive efforts to create complex multimedia scenes from vast amounts of cultural data. To address this challenge, we integrate generative AI into narrative visualization, enhancing public understanding of historical and cultural narratives through navigation, exploration, and visual analysis. To evaluate the effectiveness of our system, we conducted user studies with three domain experts and seven volunteers. Our findings suggest that ArtifactShow has significant potential to enhance public knowledge and interest in cultural heritage. Through our exploration, we developed a workflow and design guidelines for using generative AI to construct narrative visualizations for cultural heritage.

Original languageEnglish
Title of host publicationCHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400713958
DOIs
Publication statusPublished - 26 Apr 2025
Event2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025 - Yokohama, Japan
Duration: 26 Apr 20251 May 2025

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025
Country/TerritoryJapan
CityYokohama
Period26/04/251/05/25

Keywords

  • Cultural Heritage
  • Data Visualization
  • Generative AI

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