Modelling heterogeneous information spreading abilities of social network ties

被引:9
|
作者
Ou, Chengeng
Jin, Xiaolong [1 ]
Wang, Yuanzhuo
Cheng, Xueqi
机构
[1] Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Information spreading; Small world network; Random network; User attention modelling; DIFFUSION; DYNAMICS;
D O I
10.1016/j.simpat.2017.03.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Information spreading is often analyzed comparatively on small-world and random networks. Topological differences between small-world networks and random networks are believed to be main reasons that lead to various different spreading behaviours on these two types of networks. Besides those differences, the heterogeneity of spreading abilities of network ties is often overlooked. In this study, we analyze the impacts of the heterogeneity on information spreading over small-world networks and random networks. Through simulations on both artificial and realistic networks, we find that the strong heterogeneity leads to lower efficiency of spreading over small-world networks. The heterogeneity not only slows down the spreading pace, but also lengthens the life span of the information spread over small-world networks. Under such strong heterogeneity, random networks, which are affected little, are better for information spreading. However, as the heterogeneity decreases, small-world networks finally exceed random networks when regarding information spreading. We also conduct experiments to review the weak ties assumption in small-world networks. We find that the heterogeneity forces information to bypass weak ties and travels along strongly connected nodes. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:67 / 76
页数:10
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