摘要
为了提高网络舆情的监控和管理能力,需要进行网络舆情转变方向预测,提出一种模糊语义特征分析的复杂网络中舆情转变方向预测方法.构建复杂网络中舆情转变方向的大数据统计分析模型,采用模糊状态监测方法进行网络舆情转变方向的特征检测,提取复杂网络中舆情转变方向的语义特征量,分析网络舆情信息的文本摘要语义表达信息,利用抽取式摘要检测方法进行网络舆情转变方向的聚类分析,采用模糊自适应调度方法实现复杂网络中舆情转变方向预测.仿真结果表明,采用该方法复杂网络中舆情转变方向预测的准确性较高,网络环境适应性较好.
To improve the ability of monitoring and management of network public opinion,it is necessary to predict the change direction of network public opinion. A fuzzy semantic feature analysis method is proposed to predict the change direction of public opinion in complex networks. A large data statistical analysis model of changing direction of public opinion in complex network was constructed,fuzzy state monitoring method was then used to detect the feature of changing direction of network public opinion,and semantic feature quantity of changing direction of public opinion in complex network was extracted. This paper analyzes the semantic expression information of text summary of network public opinion information,uses abstract detection method to cluster analysis of network public opinion change direction,and uses fuzzy adaptive scheduling method to predict the change direction of public opinion in complex network. The simulation results show that the prediction accuracy of the change direction of public opinion is higher and the adaptability of the network environment is better.
作者
朱玉
李枫
ZHU Yu;LI Feng(Shanxi Police College,Taiyuan 030006,China)
出处
《内蒙古民族大学学报（自然科学版）》
2019年第5期396-401,共6页
Journal of Inner Mongolia Minzu University：Natural Sciences
基金
山西省“1331工程”重点学科建设计划经费资助项目(1331KSC)
山西警察学院科研创新团队建设计划资助项目
关键词
复杂网络
舆情
转变方向
预测
大数据统计
Complex network
Public opinion
Change direction
Forecast
Big data statistics
