F
Feng Wang
Researcher at Arizona State University
Publications - 10
Citations - 229
Feng Wang is an academic researcher from Arizona State University. The author has contributed to research in topics: Social media & Visual analytics. The author has an hindex of 5, co-authored 10 publications receiving 204 citations. Previous affiliations of Feng Wang include General Electric & University of Science and Technology of China.
Papers
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Proceedings ArticleDOI
Visualizing Social Media Sentiment in Disaster Scenarios
TL;DR: A novel visual analytics framework for sentiment visualization of geo-located Twitter data is proposed that provides an entropy-based metric to model sentiment contained in social media data and is further integrated into a visualization framework to explore the uncertainty of public opinion.
Proceedings ArticleDOI
Integrating predictive analytics and social media
TL;DR: This paper presents a framework for the development of predictive models utilizing social media data, which combines feature selection mechanisms, similarity comparisons and model cross-validation through a variety of interactive visualizations to support analysts in model building and prediction.
Journal ArticleDOI
Business intelligence from social media: a study from the VAST Box Office Challenge.
TL;DR: A proposed VA toolkit extracts data from Bitly and Twitter to predict movie revenue and ratings and is generalizable to other domains involving social media data, such as sales forecasting and advertisement analysis.
Journal ArticleDOI
Analyzing Entrepreneurial Social Networks with Big Data
TL;DR: The authors analyzed digitally mediated interactions using Twitter data collected about a variety of actors engaged in entrepreneurial networks for the United States over an eighteen-month period, and found that the hashtags used in this analysis (#smallbiz and #entrepreneur) do capture (albeit not exhaustively) well-known actors in entrepreneurial network, as well as important subtleties in the geography of locales engaged in these activities.
Journal ArticleDOI
A Visual Analytics Framework for Spatiotemporal Trade Network Analysis
Hong Wang,Yafeng Lu,Shade T. Shutters,Michael Steptoe,Feng Wang,Steven T. Landis,Ross Maciejewski +6 more
TL;DR: A highly coordinated, multi-view framework that utilizes anomaly detection, network analytics, and spatiotemporal visualization methods for exploring the relationship between global trade networks and regional instability is developed.