一种基于主题相似性和网络拓扑的微博社区发现方法  

Community Discovery Method Based on Users’ Interest Similarity and Social Network Structure

作　　者：王卫平[1] 范田[1] 

机构地区：[1]中国科学技术大学管理学院,合肥230026

出　　处：《计算机系统应用》2013年第6期108-113,共6页Computer Systems & Applications

摘　　要：随着微博的迅速发展和大量普及,微博社区发现已经成为新兴的研究热点.发现网络社区有助于运营商理解网络结构和用户特征,为用户提供个性化服务.目前有关社区挖掘的研究大多只关注于网络结构,忽略节点内容.本文综合考虑网络结构和节点内容,提出一种基于用户主题相似性和网络拓扑结构的微博社区发现方法.首先从微博文本中抽取用户主题,然后结合用户之间的链接关系,对它们进行基于相似性的聚类,最终获得社区结构.在真实数据集上的实验证明:所提出的方法不但能够发现潜在社区,而且还能获知社区主题.With the rapid development and a large popularity of microblogging, community discovery has become the current new research focuses, which could help the operators understand network structure and the characteristics of users, then provide users with personalized services. Most of previous study only emphasized the network structure without considering the content. The paper provides a community discovery method based on the users＇ theme similarity and network structure. Firstly, retrieve users＇ theme from their microblogging; then cluster the similar users based on the links among them and users＇ similarity; finally gain the communities. The experiments on the big data show that the method can not only find potential community, but also gain its theme.

关 键 词：社会网络 微博 社区发现 聚类 LDA 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术]