Model for multi-messages spreading over complex networks considering the relationship between messages
Model for multi-messages spreading over complex networks considering the relationship between messages
复制标题
考虑消息之间关系的复杂网络上传播的多消息模型
DOI：
10.1016/j.cnsns.2016.12.019
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发表时间：
2017-07
影响因子：
3.9
通讯作者：
Zhao Tianfang
中科院分区：
文献类型：
--
作者：
Wang Xingyuan;Zhao Tianfang
提出了一种新的消息传播模型。该模型是SIS(易感-感染-易感)模型的自然推广，其中两个具有相同接受概率的相关消息可以在节点之间传播。仅在两个消息同时作用于同一节点的意义上，其中一个消息具有比另一个消息更高的优先级。当模型中的节点采用任一消息时，该节点被称为支持者。跃迁概率允许两种支撑体以一定的速率相互转化，并与在原点周围对称间隔内离散分布的相关能级成反比。数值模拟结果表明，个体倾向于以更好的一致性来相信消息。如果消息相互冲突，则优先级较高的消息将被更多地传播，而另一条消息将被忽略。否则，两种支持的数量都将保持在一致较高的水平。此外，在连接度较低的网络中，超过一半的人会保持中立，优先级较低的消息比特权消息更难传播。本文从多报文的关联度出发，探讨了多报文的传播问题，有助于理解和预测潜在的传播趋势。
A novel messages spreading model is suggested in this paper. The model is a natural generalization of the SIS (susceptible-infective-susceptible) model, in which two relevant messages with same probability of acceptance may spread among nodes. One of the messages has a higher priority to be adopted than the other only in the sense that both messages act on the same node simultaneously. Node in the model is termed as supporter when it adopts either of messages. The transition probability allows that two kinds of supports may transform into each other with a certain rate, and it varies inversely with the associated levels which are discretely distributed in the symmetrical interval around original point. Results of numerical simulations show that individuals tend to believe the messages with a better consistency. If messages are conflicting with each other, the one with higher priority would be spread more and another would be ignored. Otherwise, the number of both supports remains at a uniformly higher level. Besides, in a network with lower connected degree, over a half of the individuals would keep neutral, and the message with lower priority becomes harder to diffuse than the prerogative one. This paper explores the propagation of multi-messages by considering their correlation degree, contributing to the understanding and predicting of the potential propagation trends.
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DOI：
10.1109/chicc.2014.6897077
发表时间：
2014-07
期刊：
Proceedings of the 33rd Chinese Control Conference
影响因子：
--
作者：
Linhe Zhu;Hongyong Zhao;Haiyan Wang
通讯作者：
Linhe Zhu;Hongyong Zhao;Haiyan Wang
影响因子：
56.9
作者：
Barabási, AL;Albert, R
通讯作者：
Albert, R
影响因子：
2.4
作者：
Trpevski, Daniel;Tang, Wallace K. S.;Kocarev, Ljupco
通讯作者：
Kocarev, Ljupco
DOI：
10.1016/j.cnsns.2011.02.032
发表时间：
2011-11
期刊：
非线性科学与数值模拟通讯(英文版)
影响因子：
--
作者：
Sun, Wen;Chen, Shihua;Xiao, Lei;Chen, Zhong;Hu, Tiesong
通讯作者：
Hu, Tiesong
DOI：
10.1515/9781400841356.349
发表时间：
1999
期刊：
--
影响因子：
--
作者：
B. McInnes;Jannene S. McBride;N. Evans;David D. Lambert;A. Andrew
通讯作者：
B. McInnes;Jannene S. McBride;N. Evans;David D. Lambert;A. Andrew