考虑用户和传播属性的节点影响力评估算法

J4 ›› 2015, Vol. 37 ›› Issue (11): 2105-2111.

考虑用户和传播属性的节点影响力评估算法

尚焱,樊欣唯，于洪

（北京邮电大学信息物理融合实验室，北京 100876）

收稿日期:2015-01-07 修回日期:2015-08-11 出版日期:2015-11-25 发布日期:2015-11-25
基金资助:
国家自然科学基金资助项目（61379114）

A novel node influence measurement algorithm based
on characteristics of users and propagation

SHANG Yan，FAN Xinwei，YU Hong

（Laboratory of CyberPhysical Systems,Beijing University of Posts and Telecommunications,Beijing 100876,China)

Received:2015-01-07 Revised:2015-08-11 Online:2015-11-25 Published:2015-11-25

摘要/Abstract

摘要：

在微博的传播过程中，关键节点起着意见领袖的作用，在社交网络中发现关键节点对舆情的分析、控制等方面是非常有意义的，作为社交网络的传播节点，用户不仅与用户本身属性有关，还与微博消息的传播属性有关。对两种属性分别选取三个指标，利用层次分析法中构造判断矩阵的方法评估各个指标的权重，将用户系数和传播系数分别作为传播网络的节点和边的权值，形成双加权的网络拓扑图，然后建立考虑用户和传播属性的影响力评估算法来计算转发节点的影响力。通过与现有算法进行比较，表明本文的算法能够更加客观准确地评估关键节点在传播过程中的重要程度。

关键词: 关键节点, 用户系数, 传播系数, 层次分析法, NodeRank算法

Abstract:

During the spreading process of microblogs, key nodes play an important role as “attitude leaders”. It is essential to figure out those key nodes for analyzing and monitoring public sentiments. As propagation nodes, users’ variety not only depends on their own characteristics, but also the characteristics of propagation. We select three indicators among two characteristics and adopt the evaluation array of the analytic hierarchy process to assess these indicators. User coefficient and propagation coefficient are used as the node weight and the edge weight respectively, thus forming a double weighted topological graph. Then we establish a novel node influence measurement algorithm of nodes based on the characteristics of users and propagation to evaluate the influence of each node. Compared with existing algorithms, the proposed algorithm can evaluate the importance of key nodes more accurately and objectively during propagation process.

Key words: key nodes;user coefficient;propagation coefficient;analytic hierarchy process;NodeRank algorithm;

尚焱,樊欣唯，于洪. 考虑用户和传播属性的节点影响力评估算法[J]. J4, 2015, 37(11): 2105-2111.

SHANG Yan，FAN Xinwei，YU Hong. A novel node influence measurement algorithm based
on characteristics of users and propagation [J]. J4, 2015, 37(11): 2105-2111.

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