Community detection in civil society online networks: Theoretical guide and empirical assessment

被引:16
|
作者
Stoltenberg, Daniela [1 ]
Maier, Daniel [2 ]
Waldherr, Annie [1 ]
机构
[1] Univ Munster, Dept Commun, Munster, Germany
[2] Free Univ Berlin, Inst Media & Commun Studies, Berlin, Germany
基金
瑞士国家科学基金会;
关键词
Hyperlink network analysis; Community detection; Cohesive subgroup; Civil society; Computational methods; HYPERLINK NETWORK; CLIMATE-CHANGE; ISSUE; COMMUNICATION; FRAMEWORK; POLICY; MEDIA;
D O I
10.1016/j.socnet.2019.07.001
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
Community detection is a fundamental challenge in the analysis of online networks. However, there is a lack of consensus regarding how to accomplish this task in a manner that acknowledges domain-specific, substantive social theory. We develop a typology of what social phenomena communities of hyperlinked actors may signify-topical similarities, ideological associations, strategic alliances, and potential user traffic-and offer recommendations for community detection grounded in these concepts. Testing procedures on a hyperlink network of the food safety movement, we demonstrate that the handling of tie directions and weights as well as algorithm choice influence which communities are ultimately detected in such a network.
引用
收藏
页码:120 / 133
页数:14
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