Emergence of blind areas in information spreading

Recently, contagion-based (disease, information, etc.) spreading on social networks has been extensively studied. In this paper, other than traditional full interaction, we propose a partial interaction based spreading model, considering that the informed individuals would transmit information to on...

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Bibliographic Details
Published in:PloS one 2014-04, Vol.9 (4), p.e95785-e95785
Main Authors: Zhang, Zi-Ke, Zhang, Chu-Xu, Han, Xiao-Pu, Liu, Chuang
Format: Article
Language:English
Subjects:
Computer and Information Sciences
Computer Simulation
Connectionism
Critical phenomena
Heterogeneity
Humans
Information Dissemination
Percolation
Physical Sciences
Size distribution
Social interactions
Social Networking
Social networks
Social organization
Social research
Social Sciences
Spreading
Studies
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Summary:Recently, contagion-based (disease, information, etc.) spreading on social networks has been extensively studied. In this paper, other than traditional full interaction, we propose a partial interaction based spreading model, considering that the informed individuals would transmit information to only a certain fraction of their neighbors due to the transmission ability in real-world social networks. Simulation results on three representative networks (BA, ER, WS) indicate that the spreading efficiency is highly correlated with the network heterogeneity. In addition, a special phenomenon, namely Information Blind Areas where the network is separated by several information-unreachable clusters, will emerge from the spreading process. Furthermore, we also find that the size distribution of such information blind areas obeys power-law-like distribution, which has very similar exponent with that of site percolation. Detailed analyses show that the critical value is decreasing along with the network heterogeneity for the spreading process, which is complete the contrary to that of random selection. Moreover, the critical value in the latter process is also larger than that of the former for the same network. Those findings might shed some lights in in-depth understanding the effect of network properties on information spreading.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0095785