基于首发信息的微博舆情热度预测模型

The Recearch of Micro-blog Public Opinion Popularity Forecasting Model Based on the Firstly Published Information

【目的/意义】通过构建数学模型,研究大数据背景下微博舆情热度预测问题。【方法/过程】分析大数据背景下的微博舆情的首发信息特征,定义首发信息影响系数,建立微博首发信息热度预测方程模型。【结果/结论】利用百度指数、清博舆情等软件,研究47个微博舆情实例分析模型特征,并用6个微博舆情案例验证模型,得出该模型根据微博首发信息的少量数据而得到较为准确的预测结果。研究成果有利于政府面对复杂微博舆情时做到"心中有数",也为进一步研究大数据背景下微博舆情预测问题提供参考。

【Purpose/significance】Through the construction of a mathematical model, a problem about the micro-blog public opinion popularity forecasting under the background of large data was studied.【Method/process】Analyze the characteristic of the firstly published information of the micro-blog public opinion under the background of big data. Define the influence coefficient of the firstly published information. Establish the micro-blog firstly published information popularity forecasting equation model.【Result/conclusion】47 micro-blog public opinion cases were studied to analyze the characteristic of this model with softwares such as Baidu Index and Qingbo Public Opinion. Through 6 micro-blog public opinion cases, this model was verified. It was concluded that this model could be used to get the accurate forecasting result according to a small amount of data about the micro-blog firstly published information. The research result was conducive to the government＇s confidence in the face of the complex micro-blog public opinion. It could also provide some references for the further research on the micro-blog public opinion forecasting under the background of big data.