Algorithmic narrative extraction deals with extracting timelines/storylines from large datasets. It helps analysts make sense of the data by reducing its complexity and making the connections and relationships between documents and ideas more explicit. By projecting the data to 2 dimensions and superimposing the narrative storyline within the projection space, this method helps to contextualize the narratives with the data, providing an alternative way of visualizing narratives beyond the traditional timelines.
Suggested papers:
Narrative Maps: An Algorithmic Approach to Represent and Extract Information Narratives
Design guidelines for narrative maps in sensemaking tasks
Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations