网络和群体的二元性:从单模网络生成双模网络的模型

IF 1.4 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY
Network Science Pub Date : 2022-04-28 DOI:10.1017/nws.2023.3
Z. Neal
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引用次数: 1

摘要

共同的成员身份、社会地位、信仰和地域可以促进社会关系的形成。双模式预测提供了一种方法,将关于个人在这类群体中的成员关系的双模式数据转换为关于他们可能的社会关系的单模式网络。在本文中,我探索了相反的过程:社会关系如何促进群体的形成,以及如何从单模网络产生双模网络。根据团队形成、俱乐部加入和组织招募的理论,我提出了三个模型来描述这些群体是如何从社会网络中的关系中产生的。我展示了这些模型可以用来生成双模网络,这些双模网络具有在经验双模社会网络中常见的特征,并且它们编码了生成它们的单模网络的特征。最后,我讨论了这些模型的局限性和关于群体形成的理论和方法的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The duality of networks and groups: Models to generate two-mode networks from one-mode networks
Shared memberships, social statuses, beliefs, and places can facilitate the formation of social ties. Two-mode projections provide a method for transforming two-mode data on individuals’ memberships in such groups into a one-mode network of their possible social ties. In this paper, I explore the opposite process: how social ties can facilitate the formation of groups, and how a two-mode network can be generated from a one-mode network. Drawing on theories of team formation, club joining, and organization recruitment, I propose three models that describe how such groups might emerge from the relationships in a social network. I show that these models can be used to generate two-mode networks that have characteristics commonly observed in empirical two-mode social networks and that they encode features of the one-mode networks from which they were generated. I conclude by discussing these models’ limitations and future directions for theory and methods concerning group formation.
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来源期刊
Network Science
Network Science SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
3.50
自引率
5.90%
发文量
24
期刊介绍: Network Science is an important journal for an important discipline - one using the network paradigm, focusing on actors and relational linkages, to inform research, methodology, and applications from many fields across the natural, social, engineering and informational sciences. Given growing understanding of the interconnectedness and globalization of the world, network methods are an increasingly recognized way to research aspects of modern society along with the individuals, organizations, and other actors within it. The discipline is ready for a comprehensive journal, open to papers from all relevant areas. Network Science is a defining work, shaping this discipline. The journal welcomes contributions from researchers in all areas working on network theory, methods, and data.
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