Follow thy neighbor: Connecting the social and the spatial networks on Twitter

被引:71
作者
Stephens, Monica [1 ]
Poorthuis, Ate [2 ]
机构
[1] SUNY Buffalo, Dept Geog, Buffalo, NY 14261 USA
[2] Univ Kentucky, Dept Geog, Lexington, KY 40506 USA
关键词
Social network analysis; Twitter; Geospatial analysis; GEOGRAPHY; PATTERNS; SPACE;
D O I
10.1016/j.compenvurbsys.2014.07.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper compares the social properties of Twitter users' networks with the spatial proximity of the networks. Using a comprehensive analysis of network density and network transitivity we found that the density of networks and the spatial clustering depends on the size of the network; smaller networks are more socially clustered and extend a smaller physical distance and larger networks are physically more dispersed with less social clustering. Additionally, Twitter networks are more effective at transmitting information at the local level. For example, local triadic connections are more than twice as likely to be transitive than those extending more than 500 km. This implies that not only is distance important to the communities developed in online social networks, but scale is extremely pertinent to the nature of these networks. Even as technologies such as Twitter enable a larger volume of interaction between spaces, these interactions do not invent completely new social and spatial patterns, but instead replicate existing arrangements. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:87 / 95
页数:9
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