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The Analysis of China’s Integrity Situation Based on Big Data 被引量:1

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摘要 In order to study deeply the prominent problems faced by China’s clean government work,and put forward effective coping strategies,this article analyzes the network information of anti-corruption related news events,which is based on big data technology.In this study,we take the news report from the website of the Communist Party of China(CPC)Central Commission for Discipline Inspection(CCDI)as the source of data.Firstly,the obtained text data is converted to word segmentation and stop words under preprocessing,and then the pre-processed data is improved by vectorization and text clustering,finally,after text clustering,the key words of clean government work is derived from visualization analysis.According to the results of this study,it shows that China’s clean government work should focus on‘the four forms of decadence’issue,and related departments must strictly crack down five categories of phenomena,such as“illegal payment of subsidies or benefits,illegal delivery of gifts and cash gift,illegal use of official vehicles,banquets using public funds,extravagant wedding ceremonies and funeral”.The results of this study are consistent with the official data released by the CCDI’s website,which also suggests that the method is feasible and effective.
出处 《Journal on Big Data》 2019年第3期117-134,共18页 大数据杂志(英文)
基金 funded by the Open Foundation for the University Innovation Platform in the Hunan Province,grant number 16K013 Hunan Provincial Natural Science Foundation of China,grant number 2017JJ2016 2016 Science Research Project of Hunan Provincial Department of Education,grant number 16C0269 Accurate crawler design and implementation with a data cleaning function,National Students innovation and entrepreneurship of training program,grant number 201811532010 This research work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province.Open project,grant number 20181901CRP03,20181901CRP04,20181901CRP05.
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