SoCS: Explorations on the Effects of Pervasive Networking on Social Relationships and Resource Planning

随着过去几年功能强大的无线设备的出现，通常为家用计算机和移动设备保留的活动之间的界限变得非常模糊。“始终在线”访问的新机会对个人与他们所形成的社区之间的交流产生了重大的社会学影响。新的网络接入引发了一系列相关的引人入胜的研究问题。无处不在的无线网络接入对年轻人，特别是大学生的社交互动有什么影响？相反，更好地了解这些社交互动会对底层无线和有线网络产生什么影响？这两个系统之间的关系是什么，即，无线网络是否真正推动了社交互动，还是社交互动推动了对无线网络的需求？该提案的智力价值将是收集高质量的长期社交网络和行为数据，然后从社会学和技术角度分析这些数据。这项工作将为圣母大学一年级本科生提供250部智能手机。该基础设施将建立在麻省理工学院之前创建第二代系统的经验教训基础上，目的是在两年内跟踪该群体的社会关系、沟通模式和行为。这项工作的更广泛影响将包括对计算机科学和社会学的跨学科贡献。这项工作将提供大量匿名数据，以改善社会和网络性能研究。

With the advent of powerful wireless devices over the last several years, the delineation between activities typically reserved for the home computer and the mobile device has blurred considerably. The new opportunities for "always on" access have significant sociological impacts with respect to communication between individuals and the communities that they form. The new network access inspires a set of related fascinating research questions. What effect does pervasive, wireless network access have on the social interactions of young adults, in particular college-aged students? Conversely, what impact would a better understanding of these social interactions have on the underlying wireless and wired networks? What is the relationship between the two systems, i.e., does the wireless network truly drive social interactions or do social interactions drive demand on the wireless network? The intellectual merit of the proposal will be to gather high quality, long-term social network and behavioral data and then to analyze the data from sociological and technical perspectives. The work will provide two hundred and fifty smart phones to a diverse cohort of first-year University of Notre Dame undergraduate students. The infrastructure will build on lessons from previous efforts at MIT to create a second-generation system for the purpose of tracking the social ties, communication patterns, and behaviors of the cohort over two years. The broader impact of the work will include inter-disciplinary contributions for both computer science and sociology. The work will make available a tremendous body of anonymized data to improve both social and network performance research.