中文摘要：

社会网络是为收集人的情感的优秀来源，这被知道。有几千微网志在每秒张贴了并且每微网志那可以包含许多用户的情感。用户的集体感情的行为与今天的社会上的大影响，因此基于用户的感情的行为为社会管理发现组好。这篇文章集中于分析在社会网络和目标的用户的感情的行为是从充分新的观点情感聚类用户的 multivariate。下列任务被完成：第一，与向量微网志的汉语的 multivariate 情感被分析，并且描述用户的感情的行为的 multivariate 时间系列被构造。Seconedly，在类似和距离类似考虑主要部件分析(PCA ) ， multivariate 情感时间系列的类似被测量。贡献能如下被总结：尽管在社会网络的不同情感被发现，用户组织。用户的感情的变化和紧张也被考虑。在有效地聚类的实验在不同的组说明用户的感情的行为特征。

英文摘要：

It is known that the social network is an excellent source for gathering the emotions of people. There are thousands of micro-blogs posted in every second and every micro-blog that may contain a variety of user＇s emotions. The users＇ collective emotional behaviors are with great impacts on today＇s societies, so it is good to find groups for society management based on users＇ emotional behavior. This article focuses on analyzing multivariate emotional behavior of users in social network and the goal is to cluster the users from a fully new perspective-emotions. The following tasks are completed： firstly, the multivariate emotion of Chinese micro-blog with vector is analyzed, and multivariate time series to describe the user＇s emotional behavior are constructed. Seconedly, considering principal component analysis （PCA） in similarity and distance similarity, the similarity of the multivariate emotion time series is measured. The contribution could be summarized as follows： groups of users though different emotions in social network are discovered. The emotional fluctuation and intensity of users are considered as well. Experiment in clustering effectively illustrates the emotional behavior characteristics of the Users in different groups.