SIA OpenIR  > 数字工厂研究室
Alternative TitleResearch on the pattern of Information Dissemination Based on Complex Networks
Thesis Advisor郑泽宇
Keyword社交网络 信息传播 网络结构 被转发概率 社区检测
Call NumberG206/Y27/2018
Degree Discipline机械制造及其自动化
Degree Name硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractBy determining the mutation in the process of message dissemination, the article finds that the content of the message is more likely to affect the spread of the message than the sender's popularity. We also find that the probability that a message will be forwarded has a threshold that affects its ability to spread, and when the probability is above the threshold the message quickly achieves mass dissemination. Thresholds are then obtained, which can be used to judge and make the message widely spread. In addition, the characteristics of the community structure of the network can make information easier to spread in local areas, and different community structures can be spread by connecting users with big betweenness. Making full use of the network's community structure will make the dissemination of information more effective. This paper applies the infectious disease propagation model(SIR) to the real-name data of Twitter and obtains a propagation threshold that can be determined by the random-walk. It is no longer a difficult parameter to measure in the model. In addition, this paper also extends the method of calculating the nuclear score in the network, so as to quickly obtain the results of network community detection, and the results used to enhance the effect of information dissemination.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
杨焕成. 基于复杂网络的信息传播规律研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2018.
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基于复杂网络的信息传播规律研究.pdf(4285KB)学位论文 开放获取CC BY-NC-SAApplication Full Text
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