Modeling Social Networks with Sampled or Missing Data
Modeling Social Networks with Sampled or Missing Data
复制标题
使用采样数据或缺失数据对社交网络进行建模
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Krista Gile
中科院分区：
文献类型：
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作者：
M. Handcock;Krista Gile
网络模型被广泛用于表示交互单元之间的关系信息以及这些关系的含义。在社交网络的研究中，最近的重点放在随机图模型上，其中节点通常表示单个社会参与者，边表示参与者之间的特定关系。大多数对社交网络模型的推断都假设网络中所有链接的存在或不存在都被完全观察到，信息是完全可靠的，并且没有测量（例如记录）错误。这在实践中显然是不正确的，因为许多网络数据是通过抽样调查收集的。此外，即使尝试人口普查，也会遗漏个体和个体之间的联系（即，不会出现在记录的数据中）。在本文中，我们开发的概念和计算理论的基础上，抽样网络信息的推理。我们首先回顾在实践中使用的网络抽样设计的形式，并考虑各种形式的设计外缺失数据。我们考虑从可能性框架的推断，并开发了一个网络数据的类型，反映了他们在这个框架内的治疗。然后，我们开发推理的社会网络模型的基础上，从自适应网络机制的信息。我们的动机和说明的想法，通过分析的效果链接跟踪抽样设计的协作网络和分析的社会关系，从全国青少年健康纵向研究的数据缺失。
Network models are widely used to represent relational information among interacting units and the implications of these relations. In studies of social networks recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent a specified relationship between the actors. Most inference for models for social networks assumes that the presence or absence of all links in the network are completely observed, that the information is completely reliable and there are no measurement (e.g. recording) errors. This is clearly not true in practice, as much network data is collected though sample surveys. In addition even if a census of a population is attempted, individuals and links between individuals are missed (i.e., do not appear in the recorded data). In this paper we develop the conceptual and computational theory for inference based on sampled network information. We first review forms of network sampling designs used in practice and consider the various forms of out-of-design missing data. We consider inference from the likelihood framework, and develop a typology of network data that reflects their treatment within this frame. We then develop inference for social network models based on information from adaptive network mechanisms. We motivated and illustrate the ideas by analyzing the effect of link-tracing sampling designs on a collaboration network and by an analysis of social relations from the National Longitudinal Study of Adolescent Health subject to missing data.