Inferring friendship network structure by using mobile phone data
- aSanta Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501;
- bMIT Media Laboratory, Massachusetts Institute of Technology, E15–383, 20 Ames Street, Cambridge, MA 02139; and
- cDepartments of Political Science and Computer Science, Northeastern University, Boston, MA 02115
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Edited by Susan Hanson, Clark University, Worcester, MA, and approved July 1, 2009 (received for review January 14, 2009)
Abstract
Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.
- engineering-social systems
- relational inference
- social network analysis
- reality mining
- relational scripts
Footnotes
- 1To whom correspondence should be addressed. E-mail: nathan{at}mit.edu
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Author contributions: N.E., A.S.P., and D.L. designed research; N.E. and A.S.P. performed research; N.E. and D.L. contributed new reagents/analytic tools; N.E. and D.L. analyzed data; and N.E. and D.L. wrote the paper.
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The authors declare no conflict of interest.
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This article is a PNAS Direct Submission.
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See Commentary on page 15099.
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This article contains supporting information online at www.pnas.org/cgi/content/full/0900282106/DCSupplemental.
