基于个人意愿的社会网络团体结构与信息检测方案

Social Community Structure and Information Detection Scheme Based on Personal Willingness

个人意愿对于形成网络社团和传播信息有着重要的影响力,因此本文提出一种基于个人意愿的社团结构与信息检测方案.该方案中的社团检测算法初次检测以融入节点属性的模块度,再次检测以兴趣度并能发现重叠社团,最后精细检测以个人意愿,本文社团检测算法(ε_CSDA)较之前的算法更有效的是可以发现重叠社团;同时,该方案建立的信息传播模型在指数模型基础上构建边特征向量(边属性)、节点特征向量(节点属性)和意愿向量(用户意愿、社团意愿和节点意愿),并以传播概率和传播延迟构建模型基本关系,从而使得该模型实现了基于个人意愿的信息传播.实验结果表明,加入个人意愿的社团检测和信息传播方案,能够保证社团检测的有效性和实用性,能够实现用户间信息传播的主动性和可靠性.

Personal willingness is one of the most important factors influencing the construction of social community and the information dissemination in social network.In this paper,we propose a social community structure and information detection scheme based on personal willingness in social network.In our proposed scheme,the social community detection algorithm uses the node attributes to detect social community structure and further find overlapping communities;the information dissemination method is based on the exponential model,which constructs the feature vector by the edge feature and the node feature,the willingness vector by the personal willingness and the community willingness,and the basic relationship by the dissemination probability and dissemination delay.Experimental results show that our proposed scheme can ensure the effectiveness of social community detection and the initiative and reliability of information dissemination.