Citizen participation workshops are widely used by the Japanese government to incorporate public inputs into policy-making. The KJ method in which participants write ideas on sticky notes and organize them on a large sheet of paper is commonly used. However, the visibility of grouped ideas decreases as the number of notes increases, hindering the interpretation and organization of discussions. To address this issue, this study proposes a hybrid analog-digital support system. After generating ideas with sticky notes, users photograph and upload the sheet. The system automatically detects and extracts notes, allowing users to group them using a simple interface and view the results in a tabular format. The evaluation experiments showed high detection accuracy using real workshop images and a fine-tuned object detection model. A user study with students indicated improved visibility compared with traditional methods. This system enhances the clarity and manageability of group work and facilitates effective citizen-driven policy-making processes.
Oyamada et al. (Thu,) studied this question.