With more sources, higher speed and broader spreading, the public opinions in the network are more difficult to be monitored and controlled. In order to improve the ability of controlling the online public opinions, it is necessary to model the process of information diffusion quantitatively so that we can understand the characteristics of information dissemination. In this paper' the mechanism of information diffusion is first analyzed from the micro perspective, considering both the structural characteristics of networks and the time efficiency of controlling. By taking the state of node into consideration, which corresponds to a user's online or offline, the traditional independent cascade mode is developed into discrete-time oriented bi-probability cascade model. Then, the process of information diffusion is analyzed and quantified from the macro perspective. The dynamic diffusion equation with the quality of information, features of the network and the impact from external platforms is established. Compared with previous studies using only model simulations or numerical fitting, the process of information diffusion in social networks is descrbed more accurately. The experimental results show various forms of information dissemination with different characteristics. Besides, it also shows that less time would be taken for information to burst out with larger size of user network, closer relationship of users and higher quality of information. These findings are helpful to predict the trend of information diffusion and make it easier to recognize important propagators in time when managing the public opinions in social networks.
WANG Yi, LIANG Xun, FU Hong-jiao, XU Zhi-ming
. Mechanism and Quantity Modeling of Information Diffusion in Social Networks[J]. Chinese Journal of Management Science, 2017
, 25(12)
: 147
-157
.
DOI: 10.16381/j.cnki.issn1003-207x.2017.12.016
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