新媒体时代风起云涌,由于具有文字短小、传播力大等特点,微博已经成为我国网民主要的上网行为之一。然而,微博上一些负面舆情信息给社会和个人带来巨大危害,越来越受到各级部门重视。为了保障校园网络的公共安全,本文设计实现了一个基于新浪微博的校园网舆情监控系统,它通过关键字匹配和朴素贝叶斯算法相结合的方法实现了微博内容的分类,然后进一步基于聚类算法实现了微博内容的热点发现,最后结合舆情数据库实现了微博舆情预警。实验结果表明,系统稳定、高效,加强了校园公共安全。 The new media era surging, because of the short text, spread and other characteristics, microblogging has become one of the main online behavior of Internet users in China. However, some negative public opinion information on Weibo has brought great harm to the society and individuals, and has been paid more and more attention by all levels of government. In order to protect the public safety of campus network, this paper designs and implements a campus network public opinion monitoring system based on Sina Weibo, which realizes the classification of Weibo content through a combination of keyword matching and naive Bayes algorithm, and then further based on Clustering algorithm to achieve the hot spot microblogging content discovery, and finally with the public opinion database to achieve microblogging public opinion early warning. The experimental results show that the system is stable and efficient, and enhances the public safety on campus.