Abstract
Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo, show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks.
Highlights
How social networks affect information transmission or information spreading is a pressing problem
If i ∈ Mt where Γit−1 is the set of agents that i follows and who switches to the accepted state at time (t − 1) and forward the information at time t to i, wji measures the internal influence due to interaction j → i, β measures the external influence due to the media, and the set Mt contains agents who received broadcasted information at time t
The model is implemented on the who-follow-whom online social network, i.e., followship network, extracted from Sina Weibo data
Summary
How social networks affect information transmission or information spreading is a pressing problem. Theoretical studies on information spreading are mostly carried out within the framework of epidemic spreading [12], where the propagation is regarded as a sequence of social interactions between infected and susceptible individuals [25, 26] We propose a diffusion model that incorporates both social interactions and media effects [27] so as to illustrate the inter-relationship between the external and internal spreading channels. Both simulation and mathematical results of the model reveal that the spreading pattern is largely determined by the event’s characteristic, as found in the empirical analyses
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