Inferring friendship network structure by using mobile phone data
Open accessAbstract
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.
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Continuously recorded NBDC data represents a mixed signal that has been used to estimate individuals' behaviors and statuses, including face-to-face social interactions, working status, mobility, and isolation and loneliness.
“The continuously recorded NBDC data represents a mixed signal that has been used to estimate individuals’ behaviors and statuses, including face-to-face social interactions [8-10], working status [11], mobility [12], and isolation and loneliness [13,14].”
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- Authors
- Eagle, N., Pentland, A. (., & Lazer, D.
- Affiliations
- Santa Fe Institute (US)
- MIT Media Lab (US)
- Northeastern University (US)
- Corresponding author
- Eagle, Nathan
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2009-09-08
- Volume
- 106
- Issue
- 36
- Pages
- 15274-15278
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2741241
- OpenAlex
- W2166692930
- Cited by
- 1,856
- References
- 21
- Citations by year
- 2026: 14 · 2025: 33 · 2024: 34 · 2023: 38 · 2022: 53 · 2021: 84 · 2020: 96 · 2019: 107 · 2018: 153 · 2017: 124 · 2016: 155 · 2015: 162 · 2014: 195 · 2013: 192 · 2012: 171
- FWCI
- 332.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- Massachusetts Institute of Technology
- Santa Fe Institute
- Topics
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Computer Networks and Communications › Opportunistic and Delay-Tolerant Networks
- Keywords
- friendship networks, mobile phone data, social network inference, physical proximity, calling patterns, self-report questionnaire, observational data
- MeSH terms
- Adult, Communication, Data Collection, Factor Analysis, Statistical, Humans, Social Behavior, Students, Observation, Friends, Cell Phone
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