Visualizing Narratives

A narrative is an ordered sequence of connected events, usually involving multiple participants. Most existing visualization techniques represent narratives as a node-link graph where a sequence of links shows the evolution of causal and temporal relationships between characters in the narrative. These techniques make a number of simplifying assumptions about the narrative structure, however. They assume that all narratives progress linearly in time, with a well defined beginning, middle, and end. They assume that all events occur in the narrative’s timeline, and that at least two participants interact at every event. Finally they assume that every narrative is complete at the time it is visualized. Thus, while existing techniques are suitable for visualizing linear narratives, they are not well suited for visualizing evolving narratives, nor for narratives with multiple timelines. In this paper we present an extension of StoryFlow, an optimization strategy for fast generation of narrative visualizations. Our technique can visualize narratives where only one participant exists within an event. We can filter events from the narrative using constraints based on characters and/or location. We present our approach using a novel visualization technique, Yarn, that represents narratives with multiple timelines. We propose ways to extend Yarn to create visualizations for both completed and evolving narratives, and to encode character properties like beliefs, sentiments, and goals to create a more informative visualization that describes a richer set of user experiences.