微博用户区域影响力识别算法及分析

摘要

Based on the Micro-blogging analysis, from a regional perspective, we researched micro-process of information diffusion. By measuring the real behavior of the user's information sharing, we constructed the network model of information listen and information forward 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 named WeiboRank like Hits to find them, and proposed a evaluation based on real measurement coverage. It is verified that compared with the other algorithms , the proposed algorithm is effective.%通过对微博客的信息传播网络进行分析和测量,从区域信息传播的角度出发,研究了微博信息传播的微观过程.通过真实测量用户的信息传播行为,构建了信息收听网络和信息转发网络模型.通过实测数据发现,在区域信息传播中少量核心节点覆盖了主要的网络信息传播行为.针对这些核心节点,提出了一种类PageRank算法的Weibo-Rank用户传播影响力识别算法,提出了基于真实测量的信息传播覆盖率的评价指标,并通过与多种社会性传统用户影响力分析算法进行对比,实证了该算法的有效性和准确性.