你在哪里,你想要什么,你能做什么:主体性地位、人格特质和社会认知在塑造自我网络规模、结构和组成中的作用

IF 1.4 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY
Network Science Pub Date : 2020-09-01 DOI:10.1017/nws.2020.6
Matthew E. Brashears, Laura Aufderheide Brashears, Nicolas L. Harder
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引用次数: 3

摘要

自我网络被认为受到以下因素的影响:由我们的主导地位(例如,种族或性别)提供的与他人交往的机会;由我们的人格特征(例如,外向或神经质)提供的个人对互动的偏好;以及由我们回忆网络信息的认知能力提供的持续管理互动的能力。然而,先前的研究无法同时检查所有三类预测因子。我们通过使用使用控制实验室设计收集的近1000名受访者的新数据集来纠正文献中的这一缺陷;使用这个数据集,我们可以同时检查主人地位、人格特征和社会认知能力对自我网络规模、结构(即密度)和组成(即多样性)的影响。我们发现,所有类型的预测因素都会以不同的方式影响我们的自我网络,并为研究人类社交能力指明了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Where you are, what you want, and what you can do: The role of master statuses, personality traits, and social cognition in shaping ego network size, structure, and composition
Abstract Ego networks are thought to be influenced by the opportunities provided to associate with others given by our master statuses (e.g., race or sex), by the preferences individuals possess for interaction given our personality traits (e.g., extroverted or neurotic), and by the capacity to manage interactions on an ongoing basis given our cognitive ability to recall network information. However, prior research has been unable to examine all three classes of predictors concurrently. We rectify this deficiency in the literature by using a novel dataset of nearly 1000 respondents collected using controlled laboratory designs; using this dataset, we can simultaneously examine the impact of master statuses, personality traits, and social cognitive competencies on ego network size, structure (i.e., density), and composition (i.e., diversity). We find that all classes of predictors influence our ego networks, though in different ways, and point to new avenues for research into human sociability.
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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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