Tracking the evolution of infrastructure systems and mass responses using publically available data

Xiangyang Guan, Cynthia Chen, Dan Work

Research output: Contribution to journalArticle

Abstract

Networks can evolve even on a short-term basis. This phenomenon is well understood by network scientists, but receive little attention in empirical literature involving real-world networks. On one hand, this is due to the deceitfully fixed topology of some networks such as many physical infrastructures, whose evolution is often deemed unlikely to occur in short term; on the other hand, the lack of data prohibits scientists from studying subjects such as social networks that seem likely to evolve on a short-term basis. We show that both networks-the infrastructure network and social network-are able to demonstrate evolutionary dynamics at the system level even in the short-term, characterized by shifting between different phases as predicted in network science. We develop a methodology of tracking the evolutionary dynamics of the two networks by incorporating flows and the microstructure of networks such as motifs. This approach is applied to the human interaction network and two transportation networks (subway and taxi) in the context of Hurricane Sandy, using publically available Twitter data and transportation data. Our result shows that significant changes in the system-level structure of networks can be detected on a continuous basis. This result provides a promising channel for real-time tracking in the future.

Original languageEnglish (US)
Article numbere0167267
JournalPloS one
Volume11
Issue number12
DOIs
StatePublished - Dec 2016

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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  • Datasets

    New York City Taxi Trip Data (2010-2013)

    Donovan, B. (Creator) & Work, D. (Creator), University of Illinois at Urbana-Champaign, May 19 2016

    Dataset

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