Research on the evolution of netizens’ comment focus in university online public opinion: KTF-BTM topic model with topic-temporal-focus framework

• Published in: Frontiers in physics 2023-08, Vol.11
• Main Authors: Zhang, Yang, Lian, Ji-Qing, Li, Ren-De, Duan, Hong-Tao
• Format: Article
• Language: English
• Subjects: BTM; microblog; social media; topic modeling; university public opinion
• ISSN: 2296-424X; 2296-424X
• DOI: 10.3389/fphy.2023.1251386

Nowadays, Study of comments in MicroBlog online public opinion is of great significance for relevant departments in managing public opinion, due to the increasing influence of online public opinion on the Internet. This paper presents a method for studying the evolutionary characteristics of netizens’ comment focus in university online public opinion. This method is based on a three-stage framework called Topic-Temporal-Focus. Firstly, in the topic mining stage, the KTF-BTM model is proposed for topic recognition, which effectively improves the quality of analysis. Secondly, in the temporal segmentation stage, time periods are divided into 4-hour intervals, and the identified topics are paired with each comment text to generate a topic-temporal list. Finally, in the focus recognition stage, the content and evolution patterns of netizens’ comment focus within shorter time sequences are explored by analyzing the data characteristics of the topic-temporal list. Experimental results show that the proposed KTF-BTM model significantly enhances topic recognition quality for short texts. The Topic-Temporal-Focus framework overcomes the challenge of sparse comment text data within shorter time periods and effectively classifies topic evolution within limited time sequences. This research work serves as a valuable contribution towards understanding the evolutionary characteristics of netizens’ focal points in university online public opinion.