Paper Info
Title
Contextifier: automatic generation of annotated stock visualizations
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.
Year
DOI
Venue
2013
10.1145/2470654.2481374
CHI
Keywords
Field
DocType
graphical salience,news online,annotated visualization,annotated information visualization,online news tool,novel system,automatic generation,contextual relevance,account visual salience,annotated stock visualization,news article,contextualizing news visualization,time series,annotation,information visualization
Data science,Automatic summarization,World Wide Web,Annotation,Information visualization,Computer science,Human–computer interaction,Salience (language)
Conference
Citations 
PageRank 
References 
22
0.79
21
Authors
3
Name
Order
Citations
PageRank
Jessica Hullman147726.51
Nicholas Diakopoulos286856.82
Eytan Adar32648281.27