Research on Public Opinion Based on Big Data

被引:0
|
作者
Shang, Songtao [1 ]
Shi, Minyong [1 ]
Shang, Wenqian [1 ]
Hong, Zhiguo [1 ]
机构
[1] Commun Univ China, Sch Comp Sci, Beijing, Peoples R China
关键词
Big Data; data mining; public opinion; Hadoop; Mahout;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Public opinion is the people's response for social phenomena, issues, hot topics, attitudes, emotions, and so on. It reflects the focus problems of the current time of the society. By analyzing the public opinion, we can infer what will happen in the next time, and give better decision support for governments and businesses. Big Data technology is becoming a powerful data analyzing tools for massive data in recent years. Hadoop is an open source massive data processing platform based on Big Data. Mahout is a data mining algorithms' set based on Hadoop, which is designed for processing large-scale and complex data. In most instances, the public opinion information contains many text messages. For many traditional text mining algorithms, it is almost impossible to handle high dimensional data concerns large-volume and complex data sets. Hence, this paper uses Mahout text mining algorithms to process public opinion information.
引用
收藏
页码:559 / 562
页数:4
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