复制
限制
计算机科学
采样(信号处理)
图形
数据挖掘
社交网络(社会语言学)
关系数据库
网络分析
网络科学
节点(物理)
领域(数学)
计量经济学
数据科学
理论计算机科学
统计
数学
复杂网络
工程类
万维网
电气工程
滤波器(信号处理)
计算机视觉
纯数学
社会化媒体
机械工程
结构工程
作者
Emily Breza,Arun G. Chandrasekhar,Tyler H. McCormick,Mengjie Pan
摘要
Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.
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