{"title":"Hadoop-based analysis model of network public opinion and its implementation","authors":"Fei Wang, Peiyu Liu, Zhenfang Zhu","doi":"10.1117/12.2502133","DOIUrl":null,"url":null,"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.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"49 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2502133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.