[Objective] This paper presents a new model for public opinion monitoring system based on Hadoop to retrieve and analyze information from the micro-blog platforms. [Methods] We first surveyed the existing technology of the public opinion monitoring systems and proposed a new model with modified algorithm. Then, we built a big data analysis platform with Hadoop to examine the model’s feasibility through experimental simulations. [Results] The proposed model can detect and retrieve public opinion data effectively. [Limitations] The Hadoop cluster was relatively small. We did not compare our model with other clustering algorithms to discuss their advantages and disadvantages. [Conclusions] The proposed model can conduct public opinion analysis with micro-blog data and provide scientific information for the policy makers to improve crisis management.
杨爱东,刘东苏. 基于Hadoop的微博舆情监控系统模型研究[J]. 现代图书情报技术, 2016, 32(5): 56-63.
Yang Aidong,Liu Dongsu. Hadoop Based Public Opinion Monitoring System for Micro-blogs. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2016.05.07.
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