TY - GEN
T1 - Contextifier
T2 - 31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013
AU - Hullman, Jessica
AU - Diakopoulos, Nicholas
AU - Adar, Eytan
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Annotation
KW - Information visualization
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=84877997602&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877997602&partnerID=8YFLogxK
U2 - 10.1145/2470654.2481374
DO - 10.1145/2470654.2481374
M3 - Conference contribution
AN - SCOPUS:84877997602
SN - 9781450318990
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 2707
EP - 2716
BT - CHI 2013
Y2 - 27 April 2013 through 2 May 2013
ER -