Research on Patient Information Demand Preference in Network Health Community based on TF-IDF Algorithm and BTM Model

Abstract

With the rapid development of information technology, the network health community has become an important way of doctor-patient communication in the new era. As the starting point of the doctor-patient communication process, patient information needs are an important basis for conducting information communication research in online health communities. In this study, we take the question data of medical patients in the "ask and answer" community from the website called "xunyiwenyao" in 2022 as samples, and the TF-IDF algorithm was applied to draw word cloud map to reveal the hot spots of patient information demand in the secondary department, apply the BTM toic model to identify the information demand topic of patients in the network health community, and extract the information demand preferences of internal medicine patients. The study found that users of patients in online health communities pay more attention to the causes and countermeasures of initial symptoms and uncomfortable symptoms, and prefer to obtain relevant information about the efficacy and side effects of medical products.