Propagating online social networks: via different kinds of weak ties
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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In this paper, we investigate the relationship between the tie strength and information propagation in online social networks (OSNs). Specifically, we propose a novel information diffusion model to simulate the information propagation in OSNs. Empirical studies through this model on various real-world online social network data sets reveal three interesting findings. First, it is the adoption of the information pushing mechanism that greatly facilitates the information propagation in OSNs. Second, some global but cost-intensive strategies, such as selecting the ties of higher betweenness centralities for information propagation, no longer have significant advantages. Third, the random selection strategy is more efficient than selecting the strong ties for information propagation in OSNs. Along this line, we provide further explanations by categorizing weak ties into positive and negative ones and reveal the special bridge effect of positive weak ties. The inverse quantitative relationship between weak ties and network clustering coefficients is also carefully studied, which finally gives reasonable explanations to the above findings. Finally, we give some business suggestions for the cost-efficient and secured information propagation in online social networks.