ClueCart: Supporting Game Story Interpretation and Narrative Inference from Fragmented Clues
Abstract
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.
Keywords
Cite
@article{arxiv.2503.06098,
title = {ClueCart: Supporting Game Story Interpretation and Narrative Inference from Fragmented Clues},
author = {Xiyuan Wang and Yi-Fan Cao and Junjie Xiong and Sizhe Chen and Wenxuan Li and Junjie Zhang and Quan Li},
journal= {arXiv preprint arXiv:2503.06098},
year = {2025}
}
Comments
In the ACM CHI conference on Human Factors in Computing Systems (CHI) 2025