  Narratives are fundamental to our perception of the world and are pervasive
in all activities that involve the representation of events in time. Yet,
modern online information systems do not incorporate narratives in their
representation of events occurring over time. This article aims to bridge this
gap, combining the theory of narrative representations with the data from
modern online systems. We make three key contributions: a theory-driven
computational representation of narratives, a novel extraction algorithm to
obtain these representations from data, and an evaluation of our approach. In
particular, given the effectiveness of visual metaphors, we employ a route map
metaphor to design a narrative map representation. The narrative map
representation illustrates the events and stories in the narrative as a series
of landmarks and routes on the map. Each element of our representation is
backed by a corresponding element from formal narrative theory, thus providing
a solid theoretical background to our method. Our approach extracts the
underlying graph structure of the narrative map using a novel optimization
technique focused on maximizing coherence while respecting structural and
coverage constraints. We showcase the effectiveness of our approach by
performing a user evaluation to assess the quality of the representation,
metaphor, and visualization. Evaluation results indicate that the Narrative Map
representation is a powerful method to communicate complex narratives to
individuals. Our findings have implications for intelligence analysts,
computational journalists, and misinformation researchers.
