Research on Internet Public Opinion Recognition Method Based on High Frequency Co-occurrence

Abstract

This paper mainly studies the dynamic identification of hot topics and their trend prediction: the identification methods of hot topics are studied from the two dimensions of content and form; the trend prediction method is completed from the two dimensions of media attention and emotional tendency. This paper develops a hot topic recognition method based on formal feature ranking. This paper compares the advantages and disadvantages of traditional methods, and proposes a high-frequency co-occurrence clustering strategy based on minimum similarity, which effectively solves the timeliness requirements of real-time dynamic hot spot recognition. Based on the recognition of hot topics, this article will jointly complete the trend prediction of hot topics from the changes in media attention and emotional orientation. We have encapsulated the hot topic recognition method based on high-frequency co-occurrence into a module and applied it in the national language and writing public opinion monitoring system.