社交网络中用户区域影响力评估算法研究

Influence Accessment Algorithms of Regional Influential Nodes in Online Social Networks

摘要: 以人人网为例对在线社交网络的分析,从区域信息传播的角度出发,研究社交网络中,信息传播的微观过程.通过真实测量用户的信息传播行为,完成用户信息传播网络的构建和测量.发现区域信息传播网络中少量核心节点覆盖了大部分的网络传播行为.针对这些核心节点,文中提出了一种基于节点传播意愿和传播能力综合考察的节点传播影响力识别算法InfluenceRank,并通过与多种相关算法进行比对,验证了算法的有效性.

Abstract: Based on the online social network analysis,from a regional perspective,we research micro-process of information diffusion.By the measuring the real behavior of the user's sharing and reading,we construct the network of information diffusion.We found that a small group of nodes can cover the most of the communication behavior of the information diffusion.Then,we proposed a recognition algorithm InfluenceRank to find them,and verify the effectiveness.