TY - GEN
T1 - NewsViews
T2 - 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014
AU - Gao, Tong
AU - Hullman, Jessica
AU - Adar, Eytan
AU - Hecht, Brent
AU - Diakopoulos, Nicholas
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - Interactive visualizations add rich, data-based context to online news articles. Geographic maps are currently the most prevalent form of these visualizations. Unfortunately, designers capable of producing high-quality, customized geovisualizations are scarce. We present NewsViews, a novel automated news visualization system that generates interactive, annotated maps without requiring professional designers. NewsViews' maps support trend identification and data comparisons relevant to a given news article. The NewsViews system leverages text mining to identify key concepts and locations discussed in articles (as well as potential annotations), an extensive repository of "found" databases, and techniques adapted from cartography to identify and create visually "interesting" thematic maps. In this work, we develop and evaluate key criteria in automatic, annotated, map generation and experimentally validate the key features for successful representations (e.g., relevance to context, variable selection, "interestingness" of representation and annotation quality).
AB - Interactive visualizations add rich, data-based context to online news articles. Geographic maps are currently the most prevalent form of these visualizations. Unfortunately, designers capable of producing high-quality, customized geovisualizations are scarce. We present NewsViews, a novel automated news visualization system that generates interactive, annotated maps without requiring professional designers. NewsViews' maps support trend identification and data comparisons relevant to a given news article. The NewsViews system leverages text mining to identify key concepts and locations discussed in articles (as well as potential annotations), an extensive repository of "found" databases, and techniques adapted from cartography to identify and create visually "interesting" thematic maps. In this work, we develop and evaluate key criteria in automatic, annotated, map generation and experimentally validate the key features for successful representations (e.g., relevance to context, variable selection, "interestingness" of representation and annotation quality).
KW - Geovisualization
KW - Interactive maps
KW - Narrative information visualization
KW - Online news
KW - Text summarization
UR - http://www.scopus.com/inward/record.url?scp=84900404817&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84900404817&partnerID=8YFLogxK
U2 - 10.1145/2556288.2557228
DO - 10.1145/2556288.2557228
M3 - Conference contribution
AN - SCOPUS:84900404817
SN - 9781450324731
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 3005
EP - 3014
BT - CHI 2014
PB - Association for Computing Machinery
Y2 - 26 April 2014 through 1 May 2014
ER -