Statistical physics research for human behaviors, complex networks, and information mining

Bing Hong Wang*, Tao Zhou, Changsong ZHOU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Integrating empirical statistics and theoretical models is a novel and promising way to study complex systems. This survey summarized recent progress on human dynamics, complex networks and information filtering, suggesting that to apply the perspectives and methods from statistical physics based on extensive empirical data and build effective dynamical models may solve some long-standing challenges, such as uncovering the hidden regularities of human behavior, revealing the rules governing the interactions between social individuals, characterizing the dynamical evolution of neural systems, digging out personalized tastes, predicting missing information, and so on.

Original languageEnglish
Pages (from-to)103-117
Number of pages15
JournalJournal of University of Shanghai for Science and Technology
Volume34
Issue number2
Publication statusPublished - Apr 2012

Scopus Subject Areas

  • Engineering(all)

User-Defined Keywords

  • Complex network
  • Human behavior dynamics
  • Information physics

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