Impact of Online Community Structure on Information Propagation: Empirical Analysis and Modeling
Zhong He, Lian-Ren Wu, Xia Chen, Ting-Jie Lu
(School of Economics and Management, Beijing University of Post and Telecommunications, Beijing 100876,China)
Abstract:
Online social networking sites (OSNS), as a popular social media platform, have been developed massively for business and research purposes. In this paper, it investigated the impact of community structure in online social network on information propagation. A SI (Susceptible-Infected) model based on community structure was proposed. In the SI model, the heterogeneity of user’s active time was taken into account. From the results, it was found that the number of links among communities determines the fraction of infected nodes. With the increase of the number of groups G, however, the fraction of infected nodes remains approximately constant. The simulation results will be of great significance: the information will last relatively short for group networks which have either a small or a large number of groups. The results can be useful for optimizing or controlling information, such as propagating rumors in online social networks.
Key words: community structure information propagation user behavior heterogeneity
DOI：10.11916/j.issn.1005-9113.2013.03.021
Clc Number:TN92
Fund:
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Impact of Online Community Structure on Information Propagation: Empirical Analysis and Modeling
本站小编 哈尔滨工业大学/2019-10-24
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