关键词: 网络舆情,时间聚类,加权,关键词,演化分析

Abstract: The rapid development of network public opinion makes the evolution of public opinion become the research hotspot,which is of great significance for the forecast of public opinion.In this paper,we started from text clustering,for the evolution of public opinion analysis process,making the K-means clustering research in time series,and got clustering center.The time-weighted weighting of word frequency statistics in clustering was made,which makes the statistical keywords more representative.Through the analysis of the keywords obtained by time clustering and time series weighted statistical method,the trend of public opinion evolution was got.The results show that the method reduces the dimension of clustering and the noise,improves the accuracy of clustering,and enhances the reliability of evolution analysis.

Key words: Network public opinion,Time clustering,Weighting,Keywords,Evolutionary analysis