Validation of a smartphone app to map social networks of proximity
Tjeerd W. Boonstra, Mark E. Larsen, Samuel Townsend, and Helen, Christensen

TL;DR
This study validates a new smartphone app for mapping social proximity networks by comparing it with sociometric badges and self-reports, highlighting its potential and current limitations in social network research.
Contribution
The paper introduces a smartphone app for proximity data collection and compares its effectiveness to traditional methods, demonstrating its feasibility and areas for improvement.
Findings
Significant association between app and badge proximity data (rho=0.17, p<0.0001).
Networks from the app and self-report are significantly correlated, with lower correlation than badges.
App's scanning rate varies by device and operating system, affecting data accuracy.
Abstract
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…
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