基于SVM的自媒体舆情反转预测研究  

Research on Prediction for Reversal of We-media Public Opinion Based on SVM

作　　者：江长斌[1] 邹悦琦 王虎[1] 张瑶源 JIANG Chang-bin;ZOU Yue-qi;WANG Hu;ZHANG Yao-yuan(School of Management,Wuhan University of Technology,Wuhan 430000,China)

机构地区：[1]武汉理工大学管理学院,湖北武汉430000

出　　处：《情报科学》2021年第4期47-53,61,共8页Information Science

基　　金：国家社会科学基金项目“大数据视域下‘隐性’政治舆情演化规律及治理路径研究”(19BSH013)。

摘　　要：【目的/意义】自媒体时代,反转舆情事件频发。研究舆情反转的影响因素,并预测舆情反转的可能,对于及早发现反转舆情,有效规避舆情反转风险有重要的现实意义。【方法/过程】分析得出舆情反转的影响因素,基于SVM构建自媒体舆情反转预测模型,运用python 3.0对33个自媒体舆情事件进行实例验证。【结果/结论】结果表明该模型具有较好的准确性和有效性,能较准确预测舆情反转的可能。【创新/局限】结合前人观点提出舆情事件性质、舆情热度、舆情首发主体权威性、舆情传播形式和网民情感倾向等七个影响因素,并通过计算进行指标量化构建预测模型。后期可从增加舆情反转的影响因素和调节模型参数两方面提升模型准确率。【Purpose/significance】Since the We-media era, reversal of public opinion events has occurred frequently. Studying the influencing factors and predicting the possibility of public opinion reversal have important practical significance for early detection and effective avoidance of the risk of public opinion reversal.【Method/process】By analyzing the influencing factors of public opinion reversal, based on SVM, a prediction model of reversal We-media public opinion is established, and with python 3.0 to verify 33 Wemedia public opinion events.【Result/conclusion】The result shows that the model has accuracy and validity, and can better predict the possibility of public opinion reversal.【Innovation/limitation】Based on previous opinions, seven factors including the nature of public opinion events, the popularity of public opinion, the authority of the first subject of the public opinion, the form of public opinion dissemination, and the emotional tendency of netizens were put forward, and the forecast model was constructed through calculation of indicators. In the later stage, the accuracy of the model can be improved by increasing the influencing factors of public opinion reversal and adjusting model parameters.

关 键 词：自媒体 舆情反转 影响因素 支持向量机 预测 

分 类 号：G206.3[文化科学—传播学]