Validation of a smartphone app to map social networks of proximity

Social network analysis is a prominent approach to investigate interpersonal relationships. Most studies use self-report data to quantify the connections between participants and construct social networks. In recent years smartphones have been used as an alternative to map networks by assessing the...

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Bibliographic Details
Published in:PloS one 2017-12, Vol.12 (12), p.e0189877-e0189877
Main Authors: Boonstra, Tjeerd W, Larsen, Mark E, Townsend, Samuel, Christensen, Helen
Format: Article
Language:English
Subjects:
Access control
Biology and Life Sciences
Bluetooth
Comparative analysis
Computer and Information Sciences
Contingency
Contingency tables
Cybernetics
Data collection
Data processing
Engineering and Technology
Feasibility studies
Generators
International conferences
Interpersonal relations
Medical research
Mental health
Methods
Methyltestosterone
Missing data
Mobile applications
Network analysis
Physical Sciences
Polls & surveys
Proximity
Sensors
Smartphones
Social interactions
Social network analysis
Social networks
Social organization
Social Sciences
Sociometry
Statistical analysis
Wearable computers
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Summary:Social network analysis is a prominent approach to investigate interpersonal relationships. Most studies use self-report data to quantify the connections between participants and construct social networks. In recent years smartphones have been used as an alternative to map networks by assessing the proximity between participants based on Bluetooth and GPS data. While most studies have handed out specially programmed smartphones to study participants, we developed an application for iOS and Android to collect Bluetooth data from participants' own smartphones. In this study, we compared the networks estimated with the smartphone app to those obtained from sociometric badges and self-report data. Participants (n = 21) installed the app on their phone and wore a sociometric badge during office hours. Proximity data was collected for 4 weeks. A contingency table revealed a significant association between proximity data (ϕ = 0.17, p
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0189877