Exploring the health care system’s representation in the media through hierarchical topic modeling

Abstract

AbstractAs a large social structure, the health care system is often reflected in media publications. This creates a significant impact on society’s attitude towards the system and the state in general. In order to predict and correct state policies, media actions, and identify media shortcomings, it is necessary to analyze the image portrayed by the media and the public’s attitude towards it. In this article, we present the results of a multidirectional analysis of a corpus of media publications related to health care. We propose a method for analyzing the information image of health care formed by the mass media based on a topic model of a text corpus. The method evaluates reader interest in various healthcare topics, the dynamics of changes in publication sentiment, and the main information trends. The article presents the results of analyzing a corpus of mass media publications in Kazakhstan from January 2020 to January 2023.

Keywords

• Health care
• mass media
• natural language processing
• topic modeling
• Chen Jenhui, Full Professor, Computer Science and Information Engineering, Chang Gung University, No. 259, Wen-Hwa 1st Road, Kweishan, Taoyuan, Taiwan
• Technology