Coupling Story to Visualization: Using Textual Analysis as a Bridge Between Data and Interpretation
This addresses the challenge for online writers and journalists in creating cohesive narrative visualizations, though it is incremental as it builds on existing NLP and visualization techniques.
The paper tackles the problem of integrating narrative text with visualizations in online journalism by proposing an automated approach that extracts narrative components from data-rich stories and links them to supporting data evidence, demonstrated through a case study in sports journalism.
Online writers and journalism media are increasingly combining visualization (and other multimedia content) with narrative text to create narrative visualizations. Often, however, the two elements are presented independently of one another. We propose an approach to automatically integrate text and visualization elements. We begin with a writer's narrative that presumably can be supported with visual data evidence. We leverage natural language processing, quantitative narrative analysis, and information visualization to (1) automatically extract narrative components (who, what, when, where) from data-rich stories, and (2) integrate the supporting data evidence with the text to develop a narrative visualization. We also employ bidirectional interaction from text to visualization and visualization to text to support reader exploration in both directions. We demonstrate the approach with a case study in the data-rich field of sports journalism.