摘要
大数据时代食品安全网络舆情的科学预警将有助于及时有效发现危机舆情,对于遏制食品安全谣言传播、促进社会和谐稳定具有重要意义。针对食品安全网络舆情的演变发展具有高度的不确定性、灰色性、模糊性等特点,基于三角模糊数确定网络舆情预警指标权重,通过建立灰色白化权函数对各指标灰色隶属度进行计算,建立基于灰色定权聚类的网络舆情预警模型,完成网络舆情等级的界定、划分与预警。通过对食品安全事件进行案例分析,验证了模型的有效性与实用性。
Scientific early warning of network public opinion on food safety in the era of big data will help discover the public opinion crisis timely and effectively,which is of great significance to curb the spread of food safety rumors and promote social harmony and stability.According to the characteristics of the development and evolution of food safety network public opinion,such as high degree of uncertainty,greyness and little information,the weights of network public opinion early warning index are determined based on the triangular fuzzy number and the whitenization weight function is constructed to calculate the grey membership degree of each index,and then the network public opinion early warning model is established based on the grey clustering to complete the definition,classification and early warning of network public opinion rating.The efficiency and practicability of the model are verified by case analysis of food safety incidents.
作者
刘路
程铁军
LIU Lu;CHENG Tiejun(School of Economics,Nanjing University of Posts and Telecommunications,Nanjing 210023)
出处
《食品工业》
CAS
2022年第12期318-323,共6页
The Food Industry
基金
国家社科基金项目(17CXW012)
教育部人文社科项目“大数据时代我国食品安全风险预警与治理研究”(16YJCZH010)。
关键词
网络舆情
三角模糊数
灰色聚类
灰色白化权函数
网络舆情预警
network public opinion
triangular fuzzy number
grey clustering
grey whitening weight function
network public opinion early warning
