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.

摘要

信息传播是在线社交网络分析的一个重要分支。在本文中，我们构建了一个新的度量，即扩散树中叶节点的比例（L-度量）来量化信息扩散模式，并研究网络类别和信息内容对这些模式的影响。对现实世界社交网络的基于模拟的实验研究表明，信息传播在不同的网络中表现出不同的模式，并且利基信息在任何类型的网络中通常都不容易传播。这些结论为进一步研究在线社交网络的管理决策提供了新的视角。