DG Comics: Semi-Automatically Authoring Graph Comics for Dynamic Graphs

TL;DR

DG Comics is a semi-automatic tool that helps users create comics from dynamic graphs by segmenting graph snapshots and providing multi-view exploration, simplifying storytelling of evolving data.

Contribution

The paper introduces DG Comics, a novel semi-automatic authoring tool with a hierarchical clustering algorithm for dynamic graph comic creation.

Findings

User study shows improved storytelling efficiency.

Expert review confirms tool's effectiveness.

Hierarchical clustering accurately segments dynamic graphs.

Abstract

Comics are an effective method for sequential data-driven storytelling, especially for dynamic graphs -- graphs whose vertices and edges change over time. However, manually creating such comics is currently time-consuming, complex, and error-prone. In this paper, we propose DG Comics, a novel comic authoring tool for dynamic graphs that allows users to semi-automatically build and annotate comics. The tool uses a newly developed hierarchical clustering algorithm to segment consecutive snapshots of dynamic graphs while preserving their chronological order. It also presents rich information on both individuals and communities extracted from dynamic graphs in multiple views, where users can explore dynamic graphs and choose what to tell in comics. For evaluation, we provide an example and report the results of a user study and an expert review.