Mining the Health Information Needs of COVID-19 Patients Based on Social Q&A Community

Abstract

AbstractCOVID-19 has become a global pandemic, and COVID-19 patients are in a medical dilemma with no effective treatment and no effective drugs. The questions and answers in the social Q&A community can reveal the characteristics and evolution rules of the health information needs of COVID-19 patients. Using the Q&A data in Baidu Zhidao (https://zhidao.baidu.com/) as the research object, using the web crawlers to capture the data, automatic topic recognition on the acquired data by constructing an LDA topic model, exploring the content of COVID-19 patients' health information needs, and revealing the change rule of Q&A publication volume and health information need topics from the time dimension. Combining statistical information such as the number of answers, the number of likes, and the level of respondents, cluster analysis is used to reveal the changing rules of social characteristics and health information need topics. By analyzing the Q&A data on COVID-19 patients in Baidu Zhidao, it is found that the topic distribution of health information needs topic is relatively concentrated. Moreover, the number of Q&A and the types of health information needs to be changed in different development periods. There are differences in social characteristics that correspond to different topics of health information needs. Through in-depth analysis of the characteristics of health information needs of COVID-19 patients in the social Q&A community, on the one hand, it is beneficial for COVID-19 patients to obtain the required health information content timely. On the other hand, it is beneficial to optimize the community information display mechanism and improve the organization of information resources.KeywordsCOVID-19Social Q&A communityHealth information need