EconPapers    
Economics at your fingertips  
 

Can multiple social ties help improve human location prediction?

Cong Li, Shumin Zhang and Xiang Li

Physica A: Statistical Mechanics and its Applications, 2019, vol. 525, issue C, 1276-1288

Abstract: Predicting the future locations of human is of vital importance in practical applications, such as the urban planning and epidemic controlling. Here we explore how to improve the location prediction accuracy by utilizing multiple human social ties. Besides the trajectories of individuals themselves, the dense social tie, i.e friends and in-roles (F&IR), and the familiar stranger (FS) social tie are also involved to design basic location predictors, according to the social-tie properties. Interestingly, we find that the human location predictor with the FS has an even higher prediction accuracy than the predictor with the F&IR social tie. Moreover, we attempt to select a proper predictor for humans with heterogeneity. We define a social-tie motif to validate the social-tie pattern of an individual and propose a multiple-social-ties (MST) location predication method. The MST predictor opens up avenues for the location prediction considering the social-tie patterns of individuals.

Keywords: Social system; Location prediction; Familiar stranger; Social tie (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119304169
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:525:y:2019:i:c:p:1276-1288

DOI: 10.1016/j.physa.2019.04.068

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:1276-1288