ClueCart: Supporting Game Story Interpretation and Narrative Inference from Fragmented Clues

要旨

Indexical storytelling is gaining popularity in video games, where the narrative unfolds through fragmented clues. This approach fosters player-generated content and discussion, as story interpreters piece together the overarching narrative from these scattered elements. However, the fragmented and non-linear nature of the clues makes systematic categorization and interpretation challenging, potentially hindering efficient story reconstruction and creative engagement. To address these challenges, we first proposed a hierarchical taxonomy to categorize narrative clues, informed by a formative study. Using this taxonomy, we designed ClueCart, a creativity support tool aimed at enhancing creators' ability to organize story clues and facilitate intricate story interpretation. We evaluated ClueCart through a between-subjects study (N=40), using Miro as a baseline. The results showed that ClueCart significantly improved creators' efficiency in organizing and retrieving clues, thereby better supporting their creative processes. Additionally, we offer design insights for future studies focused on player-centric narrative analysis.

受賞
Best Paper
著者
Xiyuan Wang
ShanghaiTech University, Shanghai, China
Yi-Fan Cao
Hong Kong University of Science and Technology, Hong Kong, China
Junjie Xiong
School of Information Science and Technology, Shanghai, China
Sizhe Chen
Chalmers University of Technology, Gothenburg , Sweden
wenxuan li
University of Southern California, Los Angeles, California, United States
Junjie Zhang
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China
Quan Li
ShanghaiTech University, Shanghai, Shanghai, China
DOI

10.1145/3706598.3713381

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713381

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Experience Together

G403
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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