Stopczynski Arkadiusz, Sekara Vedran, Sapiezynski Piotr, Cuttone Andrea, Madsen Mette My, Larsen Jakob Eg, Lehmann Sune
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Department of Anthropology, University of Copenhagen, Copenhagen, Denmark.
PLoS One. 2014 Apr 25;9(4):e95978. doi: 10.1371/journal.pone.0095978. eCollection 2014.
This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.
本文描述了一项大规模研究的开展情况,该研究旨在以高时间分辨率并跨越多年来测量多种通信渠道中的人际互动——哥本哈根网络研究。具体而言,我们使用最先进的智能手机作为社会传感器,收集了1000名紧密相连个体的面对面互动、电信、社交网络、位置及背景信息(个性、人口统计学、健康、政治)的数据。在此,我们概述相关工作,并描述推动该研究的动机和研究议程。此外,本文详细介绍了所测量的数据类型、后端和手机软件方面的技术基础设施,以及部署程序的概述。我们记录了参与者隐私程序及其基本原则。本文最后给出了数据分析的早期结果,阐明了多渠道高分辨率数据收集方法的重要性。