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Using Visualizations to Explore Network Dynamics

Bibliographic Data

ID8238638
AuthorsKar-Hai Chu (0000-0002-2486-8846), Heather Wipfli (0000-0001-9020-2033), Thomas W Valente
Year2013
Volume14
Issue1
Pages1-24
Publication date2013-01-01
Open AccessYes
TypeARTICLE
VenueJournal of Social Structure (JOURNAL)
Journal identifiersISSN: 1529-1227 • E-ISSN: 1529-1227
PublisherWalter de Gruyter GmbH (PUBLISHER • DE)
DOI10.21307/joss-2019-026
PMID25285051
OpenAlexW2308528895
LanguageEN
Citations received8
References cited36

Network analysis has become a popular tool to examine data from online social networks to politics to ecological systems. As more computing power has become available, new technology-driven methods and tools are being developed that can support larger and richer network data, including dynamic network analysis. This timely merger of abundant data and cutting edge techniques affords researchers the ability to better understand networks over time, accurately show how they evolve, find patterns of growth, or study models such as the diffusion of innovation. We combine traditional methods in social network analysis with new innovative visualizations and methods in dynamic network studies to explore an online tobacco-control community called GLOBALink, using almost twenty years of longitudinal data. We describe the methods used for the study, and perform an exploratory network study that links empirical results to real-world events

Complex network · Computer network · Data mining · Data science · Dynamic network analysis · Enhanced Data Rates for GSM Evolution · Knowledge management · Network analysis · Network dynamics · Network science · Organizational network analysis · Social media · Social network (sociolinguistics · Social network analysis · World Wide Web · Complex Network Analysis Techniques · Computer Science · Social Capital and Networks · Social Media and Politics · Artificial Intelligence

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Citations per year0.89
Citation span2017 - 2024 (8)
Highly citedNo

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