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大数据、计算社会科学以及社会网络分析中的其他最新创新。

Big data, computational social science, and other recent innovations in social network analysis.

作者信息

Tindall David, McLevey John, Koop-Monteiro Yasmin, Graham Alexander

机构信息

Department of Sociology, University of British Columbia, Vancouver, British Columbia, Canada.

Department of Knowledge Integration, University of Waterloo, Waterloo, Ontario, Canada.

出版信息

Can Rev Sociol. 2022 May;59(2):271-288. doi: 10.1111/cars.12377. Epub 2022 Mar 14.

Abstract

While sociologists have studied social networks for about one hundred years, recent developments in data, technology, and methods of analysis provide opportunities for social network analysis (SNA) to play a prominent role in the new research world of big data and computational social science (CSS). In our review, we focus on four broad topics: (1) Collecting Social Network Data from the Web, (2) Non-traditional and Bipartite/Multi-mode Networks, including Discourse and Semantic Networks, and Social-Ecological Networks, (3) Recent Developments in Statistical Inference for Networks, and (4) Ethics in Computational Network Research.

摘要

虽然社会学家研究社会网络已有约百年历史,但数据、技术和分析方法的最新发展为社会网络分析(SNA)在大数据和计算社会科学(CSS)的新研究领域发挥突出作用提供了机遇。在我们的综述中,我们聚焦于四个广泛的主题:(1)从网络收集社会网络数据;(2)非传统及二分/多模式网络,包括话语和语义网络以及社会生态网络;(3)网络统计推断的最新发展;(4)计算网络研究中的伦理问题。

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