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

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.

Authors

Institutions

Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713381
Citations
2
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
4.96

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Wenxuan Li, Yifan Cao, Xiyuan Wang, J. Z. Zhang et al.
2 citations
Artificial Intelligence in Games
4.96
article

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

Wenxuan Li, Yifan Cao, Xiyuan Wang, J. Z. Zhang, Shichun Chen, Quan Li, Junwu Xiong
article en
2 citations

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.

University of Southern California (US), Hong Kong University of Science and Technology (HK), ShanghaiTech University (CN), Chalmers University of Technology (SE), University of Hong Kong (HK)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Artificial Intelligence in Games
4.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.