基于贝叶斯网络的自媒体舆情反转预测
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摘要
[目的/意义]近年来频发的自媒体平台舆情反转事件稀释了社会信任,弱化了政府公信力,扰乱了舆情生态平衡,文章提出自媒体环境下规避网络舆情反转的方法有着重要现实意义。[方法/过程]首先从平台控制性、信息准确性、主体批判性、传播突变性四个维度识别自媒体舆情反转的影响要素,然后构建预测模型的贝叶斯结构,利用70个舆情案例数据集完成参数学习,建立自媒体舆情反转预测模型。结合3个检验样本完成模型有效性的验证,在此基础上进行原因诊断和最大可能解释。最后结合罗尔诈捐事件进行舆情反转预测。[结果/结论]模型预测结果与实际情况较吻合,提出的自媒体舆情反转预测方法具有一定应用价值。
[Purpose/significance]In recent years,frequent public opinion reversal incidents on we-media platforms have diluted social trust,weakened the credibility of government,and disturbed the ecological balance of public opinions.It is of great practical significance to propose a method of avoiding network public opinion reversion in we-media environment.[Method/process]First,the influencing factors of we-media public opinion reversion are identified from the dimensions of platform control,information accuracy,user judgment,and dissemination mutation.Then this paper constructs a Bayesian structure,and learns the parameters through 70 samples to establish a we-media public opinion reversion prediction model.The validity of the model is testified on three samples,based on which the paper makes the reason diagnosis and the most likely explanation.Finally,the model is applied to predict the public opinion reversion of Luo Er's donation fraud event.[Result/conclusion]The prediction results are basically consistent with the actual results.The method for predicting the reversal of we-media public opinion has certain application value.
[Purpose/significance]In recent years,frequent public opinion reversal incidents on we-media platforms have diluted social trust,weakened the credibility of government,and disturbed the ecological balance of public opinions.It is of great practical significance to propose a method of avoiding network public opinion reversion in we-media environment.[Method/process]First,the influencing factors of we-media public opinion reversion are identified from the dimensions of platform control,information accuracy,user judgment,and dissemination mutation.Then this paper constructs a Bayesian structure,and learns the parameters through 70 samples to establish a we-media public opinion reversion prediction model.The validity of the model is testified on three samples,based on which the paper makes the reason diagnosis and the most likely explanation.Finally,the model is applied to predict the public opinion reversion of Luo Er's donation fraud event.[Result/conclusion]The prediction results are basically consistent with the actual results.The method for predicting the reversal of we-media public opinion has certain application value.
引文
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[13]王玉龙.舆情反转:突发事件过程中网络群体极化的角色研究---基于“天价鱼事件”的分析[J].电子政务,2016(5):16-24.
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[16]AGRE G.Diagnostic bayesian networks[J].Computers and Artificial Intelligence,1996,16(1):41-56.
[17]蒋宇,兰月新.面向舆情预测的突发事件首发信息风险评估研究[J].图书与情报,2016(3):19-27.
[18]王静茹,金鑫.多媒体网络舆情危机监测指标体系构建研究[J].情报资料工作,2017(6):25-32.
[2]MAXIMILIAN P,HANSKA A,ROXANNA S.Who is reporting the protests?[J].Journalism Studies,2013,75(14):29-45.
[3]YANG C,CHING M.The third level of agenda setting in contemporary China:Minds[J].International Journal of Communication,2015,9(3):1090-1107.
[4]DYLKO I,MCCLUSKEY M.Media effects in an era of rapid technological transformation:A case of user-generated content and political participation[J].Communication Theory,2012,22(3):250-278.
[5]史安斌,杨云康.后真相时代政治传播的理论重建和路径重构[J].国际新闻界,2017,39(9):54-70.
[6]罗贤春,庞进京.基于自媒体的政务信息传播“小世界”模式[J].情报理论与实践,2016,39(6):82-87.
[7]刘旭彤.双微传播舆情反转现象形成机理及对策研究[D].济南:山东大学,2017.
[8]刘露瑶,朱国云.公众自媒体参与社会治理的法治价值研究[J].南京社会科学,2017(5):89-94.
[9]张华.网络舆情反转现象中的“参照点效应”---基于对“大学生掏鸟窝获刑十年半”微博舆情的研究[J].新闻界,2016(7):28-32.
[10]傅鹏.新闻反转剧中的媒介责任探析[D].广州:暨南大学,2015.
[11]BENKLER Y,SHAW A.Peer production:a form of collective intelligence[M].Massachusetts:The MIT Press,2015.
[12]宋全成.论自媒体的特征、挑战及其综合管制问题[J].南京社会科学,2015(3):112-120.
[13]王玉龙.舆情反转:突发事件过程中网络群体极化的角色研究---基于“天价鱼事件”的分析[J].电子政务,2016(5):16-24.
[14]王仕民,丁存霞.自媒体视域下的主流意识形态认同[J].湖北社会科学,2017(2):11-16.
[15]袁野,兰月新,张鹏,等.基于系统聚类的反转网络舆情分类及预测研究[J].情报科学,2017,35(9):54-60.
[16]AGRE G.Diagnostic bayesian networks[J].Computers and Artificial Intelligence,1996,16(1):41-56.
[17]蒋宇,兰月新.面向舆情预测的突发事件首发信息风险评估研究[J].图书与情报,2016(3):19-27.
[18]王静茹,金鑫.多媒体网络舆情危机监测指标体系构建研究[J].情报资料工作,2017(6):25-32.