ScholarGate
助手
Machine learningNetwork science

加权自我网络分析

加权自我网络分析考察了核心行动者(自我)的个人网络,并将关系强度——衡量标准包括互动频率、亲密度或资源交换——纳入边权重。它超越了简单地存在或不存在连接,从而捕捉了每种关系的重要性以及这些不同强度如何影响社会支持、信息获取或影响力等结果。

在 MethodMind 中打开即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. Marsden, P. V. (2002). Egocentric and sociocentric measures of network centrality. Social Networks, 24(4), 407–422. DOI: 10.1016/S0378-8733(02)00016-3
  2. McCarty, C., Killworth, P. D., & Rennell, J. (2007). Impact of methods for reducing respondent burden on personal network structural measures. Social Networks, 29(2), 300–315. DOI: 10.1016/j.socnet.2006.12.005

如何引用本页

ScholarGate. (2026, June 3). Weighted Ego Network Analysis (Tie-Strength-Aware Personal Network Analysis). ScholarGate. https://scholargate.app/zh/network-analysis/weighted-ego-network-analysis

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

被引用于

ScholarGateWeighted Ego Network Analysis (Weighted Ego Network Analysis (Tie-Strength-Aware Personal Network Analysis)). 于 2026-06-15 检索自 https://scholargate.app/zh/network-analysis/weighted-ego-network-analysis · 数据集: https://doi.org/10.5281/zenodo.20539026