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作 者:张文源 甘勇[2] ZHANG Wen-yuan;GAN Yong(School of Information Engineering,Guilin Institute of Infomation Technology,Guilin Guangxi 541004,China;School of Mechanical and Electrical Engineering,Guilin University of Electronic Technology,Guilin Guangxi 541004,China)
机构地区:[1]桂林信息科技学院信息工程学院,广西桂林541004 [2]桂林电子科技大学机电工程学院,广西桂林541004
出 处:《计算机仿真》2024年第11期534-538,共5页Computer Simulation
基 金:2023年广西区教育厅中青年教师科研基础能力提升项目(2023KY1682);2020年广西区教育厅高校大学生思想政治教育理论与实践研究课题项目(2020SZ014)。
摘 要:由于网络舆情信息量规模庞大,且其表达形式多样、存在大量误导性内容,使得监测难度增大,准确性较低。为此,提出一种模糊关联结合网络爬虫的网络舆情监测仿真方法。通过网络爬虫技术采集网络舆情数据,采用模糊关联规则挖掘算法将网络舆情文本数据按照词语拆分,过滤并挑选全部词语,获取关键词,挖掘网络舆情,引入扫描统计量方法实时扫描统计不同类型和主题的网络舆情,定位网络舆情发生聚集的时间段,实现网络网络舆情监测。通过仿真分析证明,所提方法可以精准监测网络舆情变化情况,网络舆情监测处理后覆盖率高达95%,误检率一直处于5%以下,可以为网络舆情良性发展提供决策支持。Due to the large scale of online public opinion information and its diverse forms of expression,as well as the presence of a large amount of misleading content,the difficulty of monitoring has increased and the accuracy is relatively low.Therefore,a simulation method for network public opinion monitoring combining fuzzy correlation and web crawlers was proposed.At first,network public opinion data was collected by web crawler technology.Then,a fuzzy association rule mining algorithm was used to split the online public opinion text data into words,filter and select all words,so that the keywords could be obtained.Moreover,network public opinion was mined,and the method of scanning statistics was introduced to scan and calculate different types and topics of network public opinion in real time.Finally,the aggregation time of network public opinion was determined.Thus,the network public opinion monitoring was achieved.The simulation analysis proves that the proposed method can accurately monitor the change of network public opinion.After the network public opinion is monitored,the coverage rate can be as high as 95%,and the false detection rate is always below 5%.This method can provide decision support for the benign development of network public opinion.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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