Suppr超能文献

利用软件加强该领域高质量大规模网络数据收集。

Using software to enhance high-quality large-scale network data collection in the field.

作者信息

Lungeanu Alina, McKnight Mark, Negron Rennie, Munar Wolfgang, Christakis Nicholas A, Contractor Noshir S

机构信息

Northwestern University, 2240 Campus Drive, Evanston, IL 60208, United States.

Yale University, 17 Hillhouse Avenue, New Haven, CT 06511, United States.

出版信息

Soc Networks. 2021 Jul;66:171-184. doi: 10.1016/j.socnet.2021.02.007.

Abstract

is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate ' ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.

摘要

是由耶鲁网络科学研究所的人性实验室创建的一个移动平台,用于在难以接触到的社区收集高质量、位置感知、离线/在线、多语言、多关系的社交网络和行为数据。受访者使用该平台通过姓名和照片来识别他们的社交联系人,这一程序在低识字率人群或名字可能相似或容易混淆的情况下特别有用。我们使用从肯尼亚两个村庄的1969名成年受访者那里收集到的社交网络数据,来证明该平台有能力提供前所未有的元数据,以监测和报告数据收集过程,包括基于调查员、一天中的时间或地点的人为变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af95/8117970/ab53aacd98f9/gr1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验