Modeling the cooperative and competitive contagions in online social networks

Modeling the cooperative and competitive contagions in online social networks
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对在线社交网络中的合作和竞争传染进行建模

DOI:
10.1016/j.physa.2017.04.129
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发表时间:
2017-10
期刊:
Physica A: Statistical Mechanics and its Applications
影响因子:
--
通讯作者:
Zhihong Li
Zhihong Li
中科院分区:
其他
文献类型:
--
作者:
Yubei Zhuang;Jiajia Chen;Zhihong Li

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社交媒体的广泛采用增加了不同信息之间的互动,这种互动包括对我们有限注意力的合作和竞争。以往的研究主要集中在完全竞争上,本文通过一个IS 1 S2 R模型,将这种相互作用扩展到既有“合作”又有“竞争”。为了探索两种不同的信息是如何相互作用的,基于SIR流行病传播模型,IS 1 S 2 R模型将代理人分为四个部分-(Ignorant-SpreaderI-SpreaderII-Stifler)。使用微博上的真实的数据。com,一个类似于Twitter的社交网站,我们发现一些参数,如衰减率,既可以影响合作扩散过程,也可以影响竞争扩散过程,而其他参数,如传染率,只影响竞争扩散过程。此外,参数的影响在竞争扩散中比在合作扩散中更为显著。
The wide adoption of social media has increased the interaction among different pieces of information, and this interaction includes cooperation and competition for our finite attention. While previous research focus on fully competition, this paper extends the interaction to be both “cooperation” and “competition”, by employing an I S 1 S 2 R model. To explore how two different pieces of information interact with each other, the I S 1 S 2 R model splits the agents into four parts-(Ignorant-Spreader I-Spreader II-Stifler), based on SIR epidemic spreading model. Using real data from Weibo. com, a social network site similar to Twitter, we find some parameters, like decaying rates, can both influence the cooperative diffusion process and the competitive process, while other parameters, like infectious rates only have influence on the competitive diffusion process. Besides, the parameters’ effect are more significant in the competitive diffusion than in the cooperative diffusion.
DOI: 10.1103/physreve.76.011503
发表时间: 2007-07
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