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Hadoop-based analysis model of network public opinion and its implementation
Author(s): Fei Wang; Peiyu Liu; Zhenfang Zhu
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Paper Abstract

In order to perform network public opinion mining effectively, this paper proposes a Hadoop-based network public opinion analysis model, which applies HDFS file service system to store massive network data distributed, providing fault tolerance and reliability assurance; As the traditional K-means clustering method is too inefficient to process massive data during the clustering process, this paper adopts MapReduce-based K-means distributed topic clustering computation method to process the massive public opinion information through multi-computer cooperation efficiently; And to obtain the information of hot network public opinion in a certain period of time by the analysis of topic heat, and verify the effectiveness of the proposed method by experiments.

Paper Details

Date Published: 26 July 2018
PDF: 10 pages
Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108281H (26 July 2018); doi: 10.1117/12.2502133
Show Author Affiliations
Fei Wang, Shandong Normal Univ. (China)
Peiyu Liu, Shandong Normal Univ. (China)
Zhenfang Zhu, Shandong Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 10828:
Third International Workshop on Pattern Recognition
Xudong Jiang; Zhenxiang Chen; Guojian Chen, Editor(s)

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