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#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media

Zhao, Jian and Cao, Nan and Wen, Zhen and Song, Yale and Lin, Yu-Ru and Collins, Christopher (2014) #FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media. IEEE Transactions on Visualization and Computer Graphics (TVCG), 20 (12). 1773 - 1782.

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Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhao, Jian
Cao, Nan
Wen, Zhen
Song, Yale
Lin, Yu-RuYURULIN@pitt.eduYURULIN0000-0002-8497-3015
Collins, Christopher
Date: December 2014
Date Type: Publication
Journal or Publication Title: IEEE Transactions on Visualization and Computer Graphics (TVCG)
Volume: 20
Number: 12
Page Range: 1773 - 1782
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Uncontrolled Keywords: advanced, machine, learning, algorithms, anomalous, information, behaviors, anomalous, information, spreading, anomalous, retweeting, threads, anomaly, detection, back-end, anomaly, detection, model, crowd, messages, data, analysis, data, analyst, capability, data, visualisation, data, visualization, Decision, making, decision-making, deeper, analysis, dynamic, crowd, behaviors, Facebook, feature, extraction, front-end, interactive, visualizations, Hurricane, Sandy, Information, visualization, Instruction, sets, interactive, visual, analysis, system, learning, (artificial, intelligence), machine, learning, Media, Message, systems, quantitative, measurements, Retweeting, threads, social, media, social, media, Websites, social, networking, (online), Social, network, services, social, signals, twitter, Visual, analytics
Article Type: Research Article
Additional Information: visual analytics; information diffusion; social media
Date Deposited: 30 Jun 2015 15:10
Last Modified: 01 Oct 2019 12:57
URI: http://d-scholarship.pitt.edu/id/eprint/25483

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