User role analysis method based on directed topological potential

Song-qing DUAN; Xing-long YU; Bin WU; Bai WANG

doi:10.3969/j.issn.1000-436x.2014.12.015

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User role analysis method based on directed topological potential

Paper | 更新时间：2024-06-05

- User role analysis method based on directed topological potential
- Communication Journal Vol. 35, Issue 12, Pages: 124-135(2014)
- 作者机构：
  
  1. 中国软件评测中心云计算促进中心，北京 100048
  2. 北京邮电大学计算机学院，北京 100876
- 作者简介：
- 基金信息：
  
  The National Basic Research Program of China (973 Program)(2013CB329603);The National Natural Science Foundation of China(71231002);The National Natural Science Foundation of China(61375058);The Program of the Co-construction with Beijing Municipal Commission of Education of China;Ministry of Education-China Mobile Research Foundation(MCM20123021)
- DOI：10.3969/j.issn.1000-436x.2014.12.015
  CLC： TP399
- Online First：2014-12，
  
  Published：25 December 2014
- 稿件说明：
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Song-qing DUAN, Xing-long YU, Bin WU, et al. User role analysis method based on directed topological potential[J]. Communication Journal, 2014, 35(12): 124-135.
DOI：

Song-qing DUAN, Xing-long YU, Bin WU, et al. User role analysis method based on directed topological potential[J]. Communication Journal, 2014, 35(12): 124-135. DOI： 10.3969/j.issn.1000-436x.2014.12.015.

摘要

真实世界中存在大量有向、加权、动态的网络。针对有向加权网络的节点角色分析问题，提出了一种基于有向拓扑势的节点角色分析方法，该方法根据节点的行为模式及局部影响力将节点划分成4种角色。然后介绍了基于节点角色的动态网络演化分析方法，它能对角色行为进行动力学建模，展示了随时间连接模式的变化，并能检测较大影响的事件。实验结果表明，本方法能有效估计节点角色并检测动态网络的演化。

Abstract

The majority of real-world networks are directed

weighted and dynamic.Aiming at the problem of node role analysis in directed weighted network

a novel node role analysis method based on directed topological potential is pro-posed

which can divide nodes into four roles based on their behavior pattern and local influence.Then

a node role-based dynamic networks evolution analysis method is introduced

which can model the dynamics of behavioral roles represent-ing the main connectivity patterns over time and detect the significant event.The experiment results indicate that pro-posed approaches can effectively estimate the node role and detect the dynamics of network evolution.

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references

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