基于灰色马尔可夫模型的网络舆情预测研究  

Research on the Prediction of Network Public Opinion Based on Grey Markov Model

作　　者：张和平[1] 陈齐海 

机构地区：[1]南昌大学经济管理学院,江西南昌330031

出　　处：《情报科学》2018年第1期75-79,共5页Information Science

摘　　要：【目的/意义】网络舆情的发展是复杂非线性的变化过程,建立有效的数理模型对网络舆情发展趋势做出准确的预测具有重要的意义。【方法/过程】首先选用网络舆情事件的百度指数构建发展趋势的时间序列指标,经过几何平均弱化缓冲算子处理后建立改进的灰色Verhulst模型预测,最后采用马尔可夫对改进的灰色Verhulst模型预测结果进行修正。【结果/结论】选取"罗一笑事件"进行案例分析,验证了本文提出的改进的灰色马尔可夫模型在网络舆情预测中的有效性。[ Purpose/significance ] The development of network public opinion is a complex and nonlinear variation process, and the establishment of effective mathematical model has important significance to make accurate prediction of develop- ment trend in network public opinion. [Method/process] Firstly, this paper uses the Baidu Index of network public event as the indicatom of time series for the event development trend. Secondly, the original data sequences are processed by Geo- metric Average Weakening Buffer Operator （GAWBO）, and an improved gray Verhulst model prediction is established. Fi- nally, this paper uses Markov model to correct the prediction results of the improved gray Verhulst model. [Result/conclu- sion] The results show that the improved gray Markov model proposed in this paper is effective in the prediction of network public opinion with the case of ＂Luo Yixiao event＂.

关 键 词：网络舆情预测 灰Verhulst模型 弱化缓冲算子 马尔可夫 

分 类 号：G206.3[文化科学—传播学]