ASU Scholarship Showcase
This growing collection consists of scholarly works authored by ASU-affiliated faculty, students and community members, and contains many open access articles. ASU-affiliated authors are encouraged to Share Your Work in the ASU Digital Repository.
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Understanding the dynamics of human movements is key to issues of significant current interest such as behavioral prediction, recommendation, and control of epidemic spreading. We collect and analyze big data sets of human movements in both cyberspace (through browsing of websites) and physical space (through mobile towers) and find a superlinear scaling relation between the mean frequency of visit〈f〉and its fluctuation σ : σ ∼〈f⟩[superscript β] with β ≈ 1.2. The probability distribution of the visiting frequency is found to be a stretched exponential function. We develop a model incorporating two essential ingredients, preferential return and exploration, and show that …
- Zhao, Zhidan, Huang, Zi-Gang, Huang, Liang, et al.
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