Web media is generally acknowledged as "the fourth media" after the newspaper, broadcast and TV. And as Web 2. 0 prevails over the internet, the web media has a form called "self-media", which means that every individual is a receiver,also it is a publisher and a forwarder at the same time. Therefore,online social networks have been formed. It has been shown that most of these networks exhibit strong modular nature (or community structure). In this paper, a community discovery algorithm is proposed based on Laplacian matrix, this algorithm convert a social network structure into Laplacian matrix, calculate its spectral and using the properties to discover the community structure from the social network. A lot of experiments have been done on real word dataset,and the experimental results show that the algorithm can discover the community structure effectively.%Web媒体被公认为继报纸、广播、电视之后的“第四媒体”.而Web2.0的迅速普及,又使当今的Web媒体呈现了一种”自媒体”形式,即每个用户既是信息的接受者,也是信息发布者和信息转发者,因此,在当今的Web上形成了在线社会网络.研究表明在线社会网络呈现出一种很强的“模块性”(”社区性”),因此,在在线社会网络中,社区发现一直是一个研究热点,即如何设计算法以发现大规模社会网络中的社区结构.文章提出了一种基于拉普拉斯矩阵的在线社会网络社区发现算法,该算法将在线社会网络转换成以拉普拉斯矩阵形式表现,通过计算该矩阵的谱并利用其性质发现社会网络上的社区结构.文章同时针对人造数据集与真实数据集进行了实验,实验结果表明本算法能够有效的发现社会网络中的社区结构.
展开▼
