Research and implementation of social hot topic detection system based on mirco-blog

Lulin Jiao, Yan Peng
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Abstract

Micro-blog as an important part of the network media has become an important access to information for Netizens. Some hot topics have an immeasurable impact on the public opinion formation and dissemination, and also potential security risks are absolutely not underestimated. Collecting the relevant data in the micro-blog can provide data base for public opinion analysis. The study, social topic detection system based on micro-blog is mainly centered on the key technologies in the information capture and the Chinese handling of micro-blog. This study invokes the API of Sina micro-blog through three kinds of capture strategy, and then uses RMM reverse maximum matching algorithm to capture the information of microblog, after this using classification of self-build public opinion to do information classification of micro-blog for structured storage. At last this study finishes the research and implement of the system based on microblog. The system has realized the hot topics of timely capture, collection, classification, storage and retrieval which lay the foundation for further public opinion analysis.
基于微博的社会热点话题检测系统的研究与实现
微博作为网络媒体的重要组成部分,已经成为网民获取信息的重要途径。一些热点话题对舆论形成和传播的影响是不可估量的,潜在的安全风险也是绝对不可低估的。在微博中收集相关数据可以为舆情分析提供数据基础。本文研究基于微博的社会话题检测系统,主要围绕微博信息捕获和中文处理中的关键技术进行研究。本研究通过三种捕获策略调用新浪微博的API,然后使用RMM反向最大匹配算法捕获微博信息,再使用自建舆情分类对微博进行信息分类,进行结构化存储。最后,本研究完成了基于微博的系统的研究与实现。该系统实现了热点话题的及时捕获、采集、分类、存储和检索,为进一步的舆情分析奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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