Contextifier: Automatic Generation of Annotated Stock Visualizations by Jessica Hullman, Nicholas Diakopoulos and Eytan Adar.
Abstract:
Online news tools—for aggregation, summarization and automatic generation—are an area of fruitful development as reading news online becomes increasingly commonplace. While textual tools have dominated these developments, annotated information visualizations are a promising way to complement articles based on their ability to add context. But the manual effort required for professional designers to create thoughtful annotations for contextualizing news visualizations is difficult to scale. We describe the design of Contextifier, a novel system that automatically produces custom, annotated visualizations of stock behavior given a news article about a company. Contextifier’s algorithms for choosing annotations is informed by a study of professionally created visualizations and takes into account visual salience, contextual relevance, and a detection of key events in the company’s history. In evaluating our system we find that Contextifier better balances graphical salience and relevance than the baseline.
The authors use a stock graph as the primary context in which to link in other news about a publicly traded company.
Other aspects of Contextifier were focused on enhancement of that primary context.
The lesson here is that a tool with a purpose is easier to hone than a tool that could be anything for just about anybody.
I first saw this at Visualization Papers at CHI 2013 by Enrico Bertini.