ABSTRACT
Information diffusion is an important branch of online social network analysis. In this paper, we construct a new metric, the proportion of leaf nodes in a diffusion tree (L-metric), to quantify information diffusion patterns, and we study the impact of the network category and information content on these patterns. Simulation-based experimental studies of real-world social networks show that information diffusion exhibits different patterns in different networks, and niche information does not typically propagate easily in any type of network. These conclusions provide a new perspective for further research on management decisions with regard to online social networks.
Disclosure statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.