Hadoop-based analysis model of network public opinion and its implementation

Fei Wang; Peiyu Liu II; Zhenfang Zhu III

doi:10.1117/12.2502133

26 July 2018 Hadoop-based analysis model of network public opinion and its implementation

Fei Wang, Peiyu Liu II, Zhenfang Zhu III

Proceedings Volume 10828, Third International Workshop on Pattern Recognition; 108281H (2018) https://doi.org/10.1117/12.2502133
Event: Third International Workshop on Pattern Recognition, 2018, Jinan, China

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.

Citation Download Citation

Fei Wang, Peiyu Liu II, and Zhenfang Zhu III "Hadoop-based analysis model of network public opinion and its implementation", Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108281H (26 July 2018); https://doi.org/10.1117/12.2502133

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