Relationship modeling and short‐term prediction analysis between public attention and teaching research

Abstract Analyzing the relationship between Internet attention and teaching research can provide a reference for extracting and identifying research hot spots in the discipline. Currently, many kinds of literature obtain social hot‐spot information based on a single platform, such as the Baidu Index, China National Knowledge Infrastructure (CNKI), and Web of Science. Still, they ignore the common information reflected between the Baidu Index platform and the professional academic platform and the lack of relationship demonstration between them. Therefore, based on the CNKI database and Baidu Index platform, the most critical data statistical analysis service platform in the Internet era, this article proposes a relationship modeling and prediction framework (RMPF). First, RMPF analyzes the relationship between public attention and teaching research from the perspective of “high school information technology” by word frequency analysis and Pearson. Second, RMPF constructs the relationship model between them using leave‐one‐out cross‐validation. Third, RMPF predicts the development of subject teaching and research using the autoregressive integrated moving average model and multiple regressions. The results show that the correlation coefficient between public attention and teaching research is more than 0.65 from the perspective of “high school information technology,” showing a strong positive correlation. In recent years, the focus of high school information technology discipline tends to be integrating multimedia technology, cloud classroom, artificial intelligence, and other technologies and disciplines. In addition, discipline literature volume growth will slow in the next 2 years, with an average annual publication of 350 articles. The overall number of literature decreased by about 120 compared with 2020. Based on the proposed RMPF, this study clarifies the relationship between subject attention and teaching research through experimental demonstration and provides an implementation framework reference for researchers of relevant literature.