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Related Experiment Videos

Correlation between social proximity and mobility similarity.

Chao Fan1,2, Yiding Liu1, Junming Huang3,4

  • 1CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.

Scientific Reports
|September 22, 2017
PubMed
Summary

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This summary is machine-generated.

Human mobility similarity is linked to online social connections. Contrary to prior research, the diversity of common friends, not their number, significantly impacts mobility patterns.

Area of Science:

  • Computational Social Science
  • Human Mobility Studies
  • Network Science

Background:

  • Human behaviors show correlations across various dimensions (individual, collective, temporal, spatial, social, geographical).
  • Rich internet data enables exploration of human mobility similarity through social network proximity.
  • Previous studies indicate a strong link between online social proximity and offline mobility similarity.

Purpose of the Study:

  • To investigate the role of common friends (number and diversity) in human mobility similarity.
  • To challenge existing findings regarding the impact of common friends on mobility patterns.
  • To enhance understanding of the coupling between online and offline human behaviors.

Main Methods:

  • Analysis of human mobility data derived from online social network proximity.

Related Experiment Videos

  • Statistical examination of the correlation between common friends and mobility similarity.
  • Comparative analysis against previous studies on social proximity and mobility.

    • Main Results:

    • The number of common friends shows no positive impact on mobility similarity.
    • The diversity of common friends plays a key role in determining mobility similarity.
    • Findings contradict previous research emphasizing the quantity of common friends.

    Conclusions:

    • Human online social diversity is a critical factor influencing offline mobility patterns.
    • This research offers a novel perspective on the relationship between online social networks and real-world behavior.
    • The findings can aid in developing improved models for predicting human behavior based on social proximity.